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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43268?offset=10</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42130/shaman-a-user-friendly-website-for-metataxonomic-analysis-from-raw-reads-to-statistical-analysis</guid>
	<pubDate>Mon, 17 Aug 2020 05:21:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42130/shaman-a-user-friendly-website-for-metataxonomic-analysis-from-raw-reads-to-statistical-analysis</link>
	<title><![CDATA[SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis]]></title>
	<description><![CDATA[<p><span>SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large variety of plots (barplot, boxplot, heatmap, &hellip;).</span><br><span>The bioinformatics treatment is based on Vsearch [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/27781170">Rognes 2016</a><span>] which showed to be both accurate and fast [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/26664811">Wescott 2015</a><span>].The statistical analysis is based on DESeq2 R package [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/20979621">Anders and Huber 2010</a><span>] which robustly identifies the differential abundant features as suggested in [</span><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974642/">McMurdie and Holmes 2014</a><span>] and [</span><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4727335/">Jonsson2016</a><span>]. SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/25516281">Love 2014</a><span>].</span><br><span>SHAMAN is compatible with standard formats for metagenomic analysis (.csv, .tsv, .biom) and figures can be downloaded in several formats. A presentation about SHAMAN is available&nbsp;</span><a href="https://github.com/aghozlane/shaman/blob/master/www/shaman_presentation.pdf">here</a><span>&nbsp;and a poster&nbsp;</span><a href="https://github.com/aghozlane/shaman/blob/master/www/shaman_poster.pdf">here</a><span>.&nbsp;</span></p>
<p><span>More at&nbsp;<a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4</a></span></p><p>Address of the bookmark: <a href="https://github.com/aghozlane/shaman" rel="nofollow">https://github.com/aghozlane/shaman</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/30440/genome-assembly-tools-and-software-part2</guid>
	<pubDate>Tue, 27 Dec 2016 16:14:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/30440/genome-assembly-tools-and-software-part2</link>
	<title><![CDATA[Genome Assembly Tools and Software - PART2 !!]]></title>
	<description><![CDATA[<p>The genome assemblers generally take a file of short sequence reads and a file of quality-value as the input. Since the quality-value file for the high throughput short reads is usually highly memory-intensive, only a few assemblers, best suited for your assembly. For the sake of computational memory saving and convenience of data inquiry, high-throughput short reads data is always initially formatted to specific data structure. Currently, existing data structure for this usage can be predominantly classified into two categories: string-based model and graph-based model.</p><p>We therefore list many genomle assembly tools here. We mainly reported for the assembly of genomes while the others are designed aiming at handling complex genomes.</p><ul>
<li><a href="http://smithlabresearch.org/software/rmap/" title="RMAP 2.1 &ndash; Short-read Mapping">RMAP 2.1 &ndash; Short-read Mapping<br /></a><a href="http://smithlabresearch.org/software/rmap/" target="_blank">RMAP</a>&nbsp;is aimed to map accurately reads from the next-generation sequencing technology. RMAP can map reads with or without error probability information (quality scores) and supports paired-end reads or bisulfite-treated reads mapping. There is no limitaions on read widths or number of mismatches. RMAP can now map more than 8 million reads in an hour at full sensitivity to 2 mismatches<br /><br /></li>
<li><a href="https://sourceforge.net/p/mira-assembler/wiki/Home/" title="MIRA 4.0.2 &ndash; Whole Genome Shotgun and EST Sequence Assembler">MIRA 4.0.2 &ndash; Whole Genome Shotgun and EST Sequence Assembler<br /></a><a href="http://sourceforge.net/p/mira-assembler/wiki/Home/" target="_blank">MIRA</a>&nbsp;(Mimicking Intelligent Read Assembly)is a whole genome shotgun and EST sequence assembler for Sanger, 454, Solexa (Illumina), IonTorrent data and PacBio (the later at the moment only CCS and error-corrected CLR reads). It can be seen as a Swiss army knife of sequence assembly developed and used in the past 12 years to get assembly jobs done efficiently &ndash; and especially accurately. That is, without actually putting too much manual work into finishing the assembly.<br /><br /></li>
<li><a href="http://www.brown.edu/Research/Istrail_Lab/hapcompass.php" title="HapCompass 0.7.7 &ndash; A Cycle-Basis Algorithm for Accurate Haplotype Assembly">HapCompass 0.7.7 &ndash; A Cycle-Basis Algorithm for Accurate Haplotype Assembly<br /></a><a href="http://www.brown.edu/Research/Istrail_Lab/hapcompass.php" target="_blank">HapCompass</a>&nbsp;for polyploid genomes can currently be used to create accurate pairwise SNP phasings.Given a set of aligned sequence reads in a SAM file and a set of variant calls in VCF format, HAPCOMPASS will assemble reads into haplotypes.<br /><br /></li>
<li><a href="http://www.csc.kth.se/~vezzi/software/" title="GAM-NGS 1.1b &ndash; Genome Assemblies Merger for Next Generation Sequencing">GAM-NGS 1.1b &ndash; Genome Assemblies Merger for Next Generation Sequencing<br /></a><a href="http://www.csc.kth.se/~vezzi/software/" target="_blank">GAM-NGS</a>&nbsp;is able to merge two or more assemblies and it rteturns an improved assembly (more contiguous and more correct). GAM-NGS shows its full potential with multi-library Illumina-based projects.<br /><br /></li>
<li><a href="http://omics.informatics.indiana.edu/GeneStitch/" title="GeneStitch 1.2.1 &ndash; Network Matching Algorithm to Gene Assembly">GeneStitch 1.2.1 &ndash; Network Matching Algorithm to Gene Assembly<br /></a><a href="http://omics.informatics.indiana.edu/GeneStitch/" target="_blank">GeneStitch</a>&nbsp;is a tool to assemble genes using network matching algorithm. Given an already-assembled dataset, it is capable of assembling contigs together to form more complete genes with the help of a reference gene set. Currently the assembly software that GeneStitch support is SOAPdenovo.<br /><br /></li>
<li><a href="http://bioen-compbio.bioen.illinois.edu/RACA/" title="RACA 0.9.1.1 &ndash; Reference-Assisted Chromosome Assembly">RACA 0.9.1.1 &ndash; Reference-Assisted Chromosome Assembly<br /></a><a href="http://bioen-compbio.bioen.illinois.edu/RACA/" target="_blank">RACA</a>&nbsp;is an algorithm to reliably order and orient sequence scaffolds generated by NGS and assemblers into longer chromosomal fragments using comparative genome information and paired-end reads.<br /><br /></li>
<li><a href="https://software.broadinstitute.org/software/discovar/blog/" title="DISCOVAR 51750 &ndash; Genome Shotgun Assembler and Variant Caller">DISCOVAR 51750 &ndash; Genome Shotgun Assembler and Variant Caller<br /></a><a href="http://www.broadinstitute.org/software/discovar/blog/" target="_blank">DISCOVAR</a>&nbsp;is a whole genome shotgun assembler and variant caller that can generate high quality assemblies and variant calls from the latest 250 base Illumina PCR-free fragment reads.<br /><br /></li>
<li><a href="http://www.seqan.de/projects/seqcons/" title="SeqCons 1.0 &ndash; de novo and reference-guided Sequence Assembly">SeqCons 1.0 &ndash; de novo and reference-guided Sequence Assembly<br /></a><a href="http://www.seqan.de/projects/seqcons/" target="_blank">&nbsp;SeqCons</a>&nbsp;(Sequence consensus) is an open source consensus computation program for Linux and Windows. The algorithm can be used for de novo and reference-guided sequence assembly.<br /><br /></li>
<li><a href="http://www.personal.psu.edu/jhm10/Vera/SoftwareC.html" title="SimAssemblyStage1/2 0.2 &ndash; Assembly Alignment of Contigs">SimAssemblyStage1/2 0.2 &ndash; Assembly Alignment of Contigs<br /></a><a href="http://www.personal.psu.edu/jhm10/Vera/SoftwareC.html" target="_blank">SimAssemblyStage1</a>: Perfectly aligns TranscriptSimulator reads to their nucleotide templates using read title inforamation, creating ideal simulated assembly of super contigs.<br /><br /></li>
<li><a href="http://www.csc.kth.se/~vezzi/software/" title="GapFiller &ndash; Closing the Gap within Paired Reads">GapFiller &ndash; Closing the Gap within Paired Reads<br /></a><a href="http://www.csc.kth.se/~vezzi/software/" target="_blank">GapFiller</a>&nbsp;is not a standard de novo assembler. It aims &ldquo;only&rdquo; at closing the gap between pairs of reads as a first step of a large number of downstream analysis<br /><br /></li>
<li><a href="http://www.sanger.ac.uk/science/tools/pagit" title="PAGIT 1.01 &ndash; Post Assembly Genome Improvement Toolkit">PAGIT 1.01 &ndash; Post Assembly Genome Improvement Toolkit<br /></a><a href="http://www.sanger.ac.uk/resources/software/pagit/" target="_blank">PAGIT</a>&nbsp;(Post Assembly Genome Improvement Toolkit) is a tools to generate automatically high quality sequence by ordering contigs, closing gaps, correcting sequence errors and transferring annotation.<br /><br /></li>
<li><a href="https://www.bsse.ethz.ch/cbg/software.html" title="ShoRAH 0.8.2 &ndash; Short Reads Assembly into Haplotypes">ShoRAH 0.8.2 &ndash; Short Reads Assembly into Haplotypes<br /></a><a href="http://www.bsse.ethz.ch/cbg/software/shorah" target="_blank">ShoRAH</a>&nbsp;is a software package that allows for inference about the structure of a population from a set of short sequence reads as obtained from ultra-deep sequencing of a mixed sample. The package contains programs that support mapping of reads to a reference genome, correcting sequencing errors by locally clustering reads in small windows of the alignment, reconstructing a minimal set of global haplotypes that explain the reads, and estimating the frequencies of the inferred haplotypes.<br /><br /></li>
<li><a href="http://www.genomics.cn/en/navigation/show_navigation?nid=2732" title="RePS 2.0 &ndash; WGS Sequence Assembler">RePS 2.0 &ndash; WGS Sequence Assembler<br /></a><a href="http://www.genomics.cn/en/navigation/show_navigation?nid=2732" target="_blank">RePS</a>&nbsp;(Repeat-masked Phrap with scaffolding), a WGS sequence assembler, that explicitly identifies exact kmer repeats from the shotgun data and removes them prior to the assembly. The established software Phrap is used to compute meaningful error probabilities for each base. Clone-end-pairing information is used to construct scaffolds that order and orient the contigs. The updated version of RePS incorporates some of the ideas introduced by Phusion on clustering<br /><br /></li>
<li><a href="http://bibiserv2.cebitec.uni-bielefeld.de/sessionTimeout.jsf" title="treecat &ndash; Phylogenetic Comparative Assembly">treecat &ndash; Phylogenetic Comparative Assembly<br /></a><a href="http://bibiserv2.cebitec.uni-bielefeld.de/cgcat?id=cgcat_treecat" target="_blank">treecat</a>&nbsp;(phylogenetic tree based contig arrangement tool) takes several genomes and their relationships in a phylogenetic tree into account to estimate a possible ordering of the contigs.<br /><br /></li>
<li><a href="http://alumni.cs.ucr.edu/~liw/isolasso.html" title="IsoLasso 2.6.1 &ndash; A LASSO Regression Approach to RNA-Seq Based Transcriptome Assembly">IsoLasso 2.6.1 &ndash; A LASSO Regression Approach to RNA-Seq Based Transcriptome Assembly<br /></a><a href="http://alumni.cs.ucr.edu/~liw/isolasso.html" target="_blank">IsoLasso</a>&nbsp;is an algorithm to assemble transcripts and estimate their expression levels from RNA-Seq reads.<br /><br /></li>
<li><a href="http://alumni.cs.ucr.edu/~liw/cem.html" title="CEM 0.9.1 &ndash; Transcriptome Assembly and Isoform Expression Level Estimation from Biased RNA-Seq Reads">CEM 0.9.1 &ndash; Transcriptome Assembly and Isoform Expression Level Estimation from Biased RNA-Seq Reads<br /></a><a href="http://alumni.cs.ucr.edu/~liw/cem.html" target="_blank">CEM</a>&nbsp;is an algorithm to assemble transcripts and estimate their expression levels from RNA-Seq reads.<br /><br /></li>
<li><a href="http://alan.cs.gsu.edu/NGS/?q=malta" title="MaLTA &ndash; Transcriptome Assembly and Quantification from Ion Torrent RNA-Seq data">MaLTA &ndash; Transcriptome Assembly and Quantification from Ion Torrent RNA-Seq data<br /></a><a href="http://alan.cs.gsu.edu/NGS/?q=malta" target="_blank">MaLTA</a>&nbsp;is a method for simultaneous transcriptome assembly and quantification from Ion Torrent RNA-Seq data.<br /><br /></li>
<li><a href="http://amos.sourceforge.net/wiki/index.php/AMOS" title="AMOS 3.1.0 &ndash; Whole Genome Shotgun Assembler">AMOS 3.1.0 &ndash; Whole Genome Shotgun Assembler<br /></a><a href="http://amos.sourceforge.net/wiki/index.php/AMOS" target="_blank">AMOS</a>&nbsp;(<strong>A</strong><strong>M</strong>odular,&nbsp;<strong>O</strong>pen-<strong>S</strong>ource)&nbsp;consortium is committed to the development of open-source whole genome assembly software. The project acronym (AMOS) represents our primary goal &mdash; to produce A Modular, Open-Source whole genome assembler.Open-source so that everyone is welcome to contribute and help build outstanding assembly tools, and modular in nature so that new contributions can be easily inserted into an existing assembly pipeline. This modular design will foster the development of new assembly algorithms and allow the AMOS project to continually grow and improve in hopes of eventually becoming a widely accepted and deployed assembly infrastructure. In this sense, AMOS is both a design philosophy and a software system.<br /><br /></li>
<li><a href="http://amos.sourceforge.net/wiki/index.php/AutoEditor" title="AutoEditor 1.20 &ndash; Automated Correction of Genome Sequence Errors">AutoEditor 1.20 &ndash; Automated Correction of Genome Sequence Errors<br /></a><a href="http://amos.sourceforge.net/wiki/index.php/AutoEditor" target="_blank">AutoEditor</a>&nbsp;is a tool for correcting sequencing and basecaller errors using sequence assembly and chromatogram data. On average AutoEditor corrects 80% of erroneous base calls, with an accuracy of 99.99%.This in turn improves the overall accuracy of genome sequences and facilitates the use of these sequences for polymorphism discovery.<br /><br /></li>
<li><a href="http://www.csd.uwo.ca/~ilie/SAGE/" title="SAGE &ndash; String Graph Assembly of GEnomes">SAGE &ndash; String Graph Assembly of GEnomes<br /></a><a href="http://www.csd.uwo.ca/~ilie/SAGE/" target="_blank">SAGE</a>&nbsp;is a new string-overlap graph-based de novo genome assembler.<br /><br /></li>
<li><a href="http://omega.omicsbio.org/" title="Omega 1.0.2 &ndash; Overlap-graph de novo Assembler for Metagenomics">Omega 1.0.2 &ndash; Overlap-graph de novo Assembler for Metagenomics<br /></a><a href="http://omega.omicsbio.org/" target="_blank">Omega</a>&nbsp;is a software for assembling and scaffolding Illumina sequencing data of microbial communities.<br /><br /></li>
<li><a href="http://www.compgenome.org/TCGA-Assembler/" title="TCGA-Assembler 1.0.3 &ndash; Open-Source Software for Retrieving and Processing TCGA Data">TCGA-Assembler 1.0.3 &ndash; Open-Source Software for Retrieving and Processing TCGA Data<br /></a><a href="http://www.compgenome.org/TCGA-Assembler/" target="_blank">TCGA-Assembler</a>&nbsp;is an open-source, freely available tool that automatically downloads, assembles, and processes public The Cancer Genome Atlas (TCGA) data, to facilitate downstream data analysis by relieving investigators from the burdens of data preparation.<br /><br /></li>
<li><a href="http://sammate.sourceforge.net/" title="SAMMate 2.7.4 / assemblySAM 1.1 &ndash;  Processing Short Read Alignments in SAM/BAM format / RNA-Seq Assembly and Analysis">SAMMate 2.7.4 / assemblySAM 1.1 &ndash; Processing Short Read Alignments in SAM/BAM format / RNA-Seq Assembly and Analysis<br /></a>
<p><a href="http://sammate.sourceforge.net/" target="_blank">SAMMate</a>&nbsp;is an open source GUI software suite to process RNA-Seq data. It is composed of two modules: assemblySAM and SAMMate.</p>
<p>assemblySAM employs a novel method to localize and assemble RNA-seq reads into RNA transcript sequences.<br /><br /></p>
</li>
<li><a href="http://www.cs.tau.ac.il/~bchor/StringGraph/" title="StringGraph beta &ndash; String Graph Construction Using Incremental Hashing">StringGraph beta &ndash; String Graph Construction Using Incremental Hashing<br /></a><a href="http://www.cs.tau.ac.il/~bchor/StringGraph/" target="_blank">StringGraph</a>&nbsp;is a novel, hash based method for constructing the string graph.<br /><br /></li>
<li><a href="http://mindthegap.genouest.org/" title="MindTheGap 1.0.0 &ndash; Detection and Assembly of Insertion Variants">MindTheGap 1.0.0 &ndash; Detection and Assembly of Insertion Variants<br /></a><a href="http://mindthegap.genouest.org/" target="_blank">MindTheGap</a>&nbsp;is a software that performs detection and assembly of DNA insertion variants in NGS read datasets with respect to a reference genome.<br /><br /></li>
<li><a href="http://cbcb.umd.edu/software/metAMOS" title="MetAMOS 1.5rc3 &ndash; Metagenomic Assembly pipeline for AMOS">MetAMOS 1.5rc3 &ndash; Metagenomic Assembly pipeline for AMOS<br /></a><a href="http://cbcb.umd.edu/software/metAMOS" target="_blank">MetAMOS</a>&nbsp;is an open source and modular metagenomic assembly and analysis pipeline. MetAMOS represents an important step towards fully automated metagenomic analysis, starting with next-generation sequencing reads and producing genomic scaffolds, open-reading frames and taxonomic or functional annotations.<br /><br /></li>
<li><a href="http://impact.crhc.illinois.edu/projects.aspx#tiger" title="TIGER &ndash; DNA Sequence Assembly">TIGER &ndash; DNA Sequence Assembly<br /></a><a href="http://impact.crhc.illinois.edu/projects.aspx#tiger" target="_blank">Tiger</a>&nbsp;is a novel de novo assembly framework &nbsp;which adapts to available computing resources by iteratively decomposing the assembly problem into sub-problems.<br /><br /></li>
<li><a href="https://github.com/baoe/AlignGraph" title="AlignGraph &ndash; Secondary de novo Genome Assembly guided by closely related References">AlignGraph &ndash; Secondary de novo Genome Assembly guided by closely related References<br /></a><a href="https://github.com/baoe/AlignGraph" target="_blank">AlignGraph</a>&nbsp;is a software that extends and joins contigs or scaffolds by reassembling them with help provided by a reference genome of a closely related organism.<br /><br /></li>
<li><a href="http://compbio.cs.toronto.edu/hapsembler/scarpa.html" title="scarpa 0.241 &ndash; Scaffolding Reads with Practical Algorithms">scarpa 0.241 &ndash; Scaffolding Reads with Practical Algorithms<br /></a><a href="http://compbio.cs.toronto.edu/hapsembler/scarpa.html" target="_blank">Scarpa</a>&nbsp;is a stand-alone scaffolding tool for NGS data. It can be used together with virtually any genome assembler and any NGS read mapper that supports SAM format. Other features include support for multiple libraries and an option to estimate insert size distributions from data.<br /><br /></li>
<li><a href="http://genetics.cs.ucla.edu/vga/" title="VGA v1 &ndash; Viral Genome Assembler">VGA v1 &ndash; Viral Genome Assembler<br /></a><a href="http://genetics.cs.ucla.edu/vga/" target="_blank">VGA</a>&nbsp;is a method for accurate assembly of a heterogeneous viral population consisting of individuals viral genomes (also known as quasi-species).<br /><br /></li>
<li><a href="https://cbcl.ics.uci.edu//doku.php/software#genomix" title="Genomix 0.2.11 &ndash; Parallel Genome Assembly using Hyracks">Genomix 0.2.11 &ndash; Parallel Genome Assembly using Hyracks<br /></a><a href="https://cbcl.ics.uci.edu//doku.php/software#genomix" target="_blank">Genomix</a>&nbsp;is a parallel genome assembly system built from the ground up with scalability in mind. It can assemble large and high-coverage genomes from fastq files in a short time and produces assemblies similar to Velvet or Ray in quality.<br /><br /></li>
<li><a href="http://shendurelab.github.io/LACHESIS/" title="LACHESIS &ndash; Genome Assembly with Contact Probability Maps">LACHESIS &ndash; Genome Assembly with Contact Probability Maps<br /></a><a href="http://shendurelab.github.io/LACHESIS/" target="_blank">LACHESIS</a>&nbsp;is method that exploits contact probability map data (e.g. from Hi-C) for chromosome-scale de novo genome assembly.<br /><br /></li>
<li><a href="http://www.cmbb.arizona.edu/?page_id=312" title="KGBassembler 1.2 &ndash; Karyotype-based Genome Assembler for Brassicaceae Species">KGBassembler 1.2 &ndash; Karyotype-based Genome Assembler for Brassicaceae Species<br /></a><a href="http://www.cmbb.arizona.edu/?page_id=312" target="_blank">KGBassembler</a>&nbsp;(Brassicaceae genome assembler) is a C++ based tool for assembling contigs and/or scaffolds to full chromosomes based on the karyotype maps of Brassicaceae species and without the need of genetic and physical maps.<br /><br /></li>
<li><a href="https://sourceforge.net/projects/autoassemblyd/" title="AutoAssemblyD 0.1 &ndash; Graphical User Interface system for several Genome Assembler">AutoAssemblyD 0.1 &ndash; Graphical User Interface system for several Genome Assembler<br />The&nbsp;</a><a href="http://sourceforge.net/projects/autoassemblyd/" target="_blank">AssemblyD</a>&nbsp;is a software which performed the local and remote genome assembly by several assemblers based on an XML Template which can replace the large command lines required by most assemblers.<a href="http://www.mybiosoftware.com/autoassemblyd-0-1-graphical-user-interface-system-for-several-genome-assembler.html" title="AutoAssemblyD 0.1 &ndash; Graphical User Interface system for several Genome Assembler"><br /><br /></a></li>
<li><a href="http://bio.cs.put.poznan.pl/programs/519227629dfb89a7fa000001" title="SR-ASM &ndash; DNA Assembly of the Short Sequences coming from 454 sequencer">SR-ASM &ndash; DNA Assembly of the Short Sequences coming from 454 sequencer<br /></a><a href="http://bio.cs.put.poznan.pl/programs/519227629dfb89a7fa000001" target="_blank">SR-ASM</a>&nbsp;(Short Reads ASseMbly) algorithm is designed for DNA assembly of the short sequences coming from 454 sequencers.<a href="http://www.mybiosoftware.com/sr-asm-dna-assembly-short-sequences-coming-454-sequencer.html" title="SR-ASM &ndash; DNA Assembly of the Short Sequences coming from 454 sequencer"><br /><br /></a></li>
<li><a href="http://www.bx.psu.edu/miller_lab/" title="YASRA 2.33 &ndash; Yet Another Short Read Assembler">YASRA 2.33 &ndash; Yet Another Short Read Assembler<br /></a><a href="http://www.bx.psu.edu/miller_lab/" target="_blank">YASRA</a>&nbsp;performs comparative assembly of short reads using a reference genome, which can differ substantially from the genome being sequenced.<a href="http://www.mybiosoftware.com/yasra-2-32-short-read-assembler.html" title="YASRA 2.33 &ndash; Yet Another Short Read Assembler"><br /><br /></a></li>
<li><a href="http://derisilab.ucsf.edu/software/price/index.html" title="PRICE 1.2 &ndash; de novo Genome Assembler">PRICE 1.2 &ndash; de novo Genome Assembler<br /></a><a href="http://derisilab.ucsf.edu/software/price/index.html" target="_blank">PRICE</a>&nbsp;(Paired-Read Iterative Contig Extension) is a de novo genome assembler implemented in C++. Its name describes the strategy that it implements for genome assembly: PRICE uses paired-read information to iteratively increase the size of existing contigs. Initially, those contigs can be individual reads from a subset of the paired-read dataset, non-paired reads from sequencing technologies that provide non-paired data, or contigs that were output from a prior run of PRICE or any other&nbsp;<a href="http://www.mybiosoftware.com/price-0-18-de-novo-genome-assembler.html" title="PRICE 1.2 &ndash; de novo Genome Assembler"><br /><br /></a></li>
<li><a href="https://sc932.github.com/ALE/" title="ALE 20130717 &ndash; Assembly Likelihood Estimator">ALE 20130717 &ndash; Assembly Likelihood Estimator<br /></a><a href="http://sc932.github.com/ALE/" target="_blank">ALE</a>&nbsp;is a probabalistic framework for determining the likelihood of an assembly given the data (raw reads) used to assemble it. It allows for the rapid discovery of errors and comparisons between similar assemblies.<a href="http://www.mybiosoftware.com/ale-assembly-likelihood-estimator.html" title="ALE 20130717 &ndash; Assembly Likelihood Estimator"><br /><br /></a></li>
<li><a href="https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE" title="SSPACE 3.0 &ndash; Scaffolding pre-assembled Contigs using Paired-read data">SSPACE 3.0 &ndash; Scaffolding pre-assembled Contigs using Paired-read data<br /></a><a href="http://www.baseclear.com/lab-products/bioinformatics-tools/sspace-standard/" target="_blank">SSPACE</a>&nbsp;(SSAKE-based Scaffolding of Pre-Assembled Contigs after Extension) is a stand-alone program for scaffolding pre-assembled contigs using paired-read data. It is unique in offering the possibility to manually control the scaffolding process. By using the distance information of paired-end and/or matepair data, SSPACE is able to assess the order, distance and orientation of your contigs and combine them into scaffolds. Currently we offer this as a command-line tool in Perl. The input data is given by pre-assembled contig sequences (FASTA) and NGS paired-read data (FASTA or FASTQ). The final scaffolds are provided in FASTA format.<a href="http://www.mybiosoftware.com/sspace-1-2-scaffolding-pre-assembled-contigs-paired-read-data.html" title="SSPACE 3.0 &ndash; Scaffolding pre-assembled Contigs using Paired-read data"><br /><br /></a></li>
<li><a href="http://www.sanger.ac.uk/science/tools/image" title="IMAGE 2.4.1 &ndash; Iterative Mapping and Assembly for Gap Elimination">IMAGE 2.4.1 &ndash; Iterative Mapping and Assembly for Gap Elimination<br /></a><a href="http://www.sanger.ac.uk/resources/software/pagit/#IMAGE" target="_blank">IMAGE</a>&nbsp;( Iterative Mapping and Assembly for Gap Elimination) is a software designed to close gaps in any draft assembly using Illumina paired end reads. IMAGE is best described in several stages: aligning of Illumina reads at contig ends; local assembly of reads into new contigs; reference contigs are extended or merged; iterating the whole process to extend and merge more contigs.<a href="http://www.mybiosoftware.com/image-2-3-iterative-mapping-assembly-gap-elimination.html" title="IMAGE 2.4.1 &ndash; Iterative Mapping and Assembly for Gap Elimination"><br /><br /></a></li>
<li><a href="https://www.hgsc.bcm.edu/software/atlas-gapfill" title="ATLAS GapFill 2.2 &ndash; Deals with the Repetitive Gap Assembly problem">ATLAS GapFill 2.2 &ndash; Deals with the Repetitive Gap Assembly problem<br /></a><a href="https://www.hgsc.bcm.edu/software/atlas-gapfill" target="_blank">ATLAS GapFill</a>&nbsp;deals with the repetitive gap assembly problem by using the unique gap-flanking sequences to group reads and convert the problem to a local assembly task. Localizing the assembly reduces the numbers of repeats in the assembly, allows more data to be incorporated, and allows for gaps to be filled.<a href="http://www.mybiosoftware.com/atlas-gapfill-2-2-deals-repetitive-gap-assembly-problem.html" title="ATLAS GapFill 2.2 &ndash; Deals with the Repetitive Gap Assembly problem"><br /><br /></a></li>
<li><a href="https://www.hgsc.bcm.edu/software/atlas-whole-genome-assembly-suite" title="Atlas 2005 &ndash; Whole Genome Assembly Suite">Atlas 2005 &ndash; Whole Genome Assembly Suite<br /></a><a href="https://www.hgsc.bcm.edu/software/atlas-whole-genome-assembly-suite" target="_blank">Atlas</a>&nbsp;is a collection of software tools to facilitate the assembly of large genomes from whole genome shotgun reads, or a combination of whole genome shotgun reads and BAC or other localized reads.<a href="http://www.mybiosoftware.com/atlas-2005-genome-assembly-suite.html" title="Atlas 2005 &ndash; Whole Genome Assembly Suite"><br /><br /></a></li>
<li><a href="http://bio.math.berkeley.edu/cgal/" title="CGAL 0.9.6b &ndash; Computing Genome Assembly Likelihoods">CGAL 0.9.6b &ndash; Computing Genome Assembly Likelihoods<br /></a><a href="http://bio.math.berkeley.edu/cgal/" target="_blank">CGAL</a>&nbsp;is a tool for computing genome assembly likelihoods. It computes the likelihood of reads with respect to the assembly and a statistical model which can be used as a metric for evaluating assemblies.<a href="http://www.mybiosoftware.com/cgal-0-9-6-computing-genome-assembly-likelihoods.html" title="CGAL 0.9.6b &ndash; Computing Genome Assembly Likelihoods"><br /><br /></a></li>
<li><a href="https://github.com/lh3/fermi" title="Fermi 1.1 &ndash; WGS de novo Assembler based on the FMD-index for large Genomes">Fermi 1.1 &ndash; WGS de novo Assembler based on the FMD-index for large Genomes<br /></a><a href="https://github.com/lh3/fermi" target="_blank">Fermi</a>&nbsp;is a de novo assembler for Illumina reads from whole-genome short-gun sequencing. It also provides tools for error correction, sequence-to-read alignment and comparison between read sets. It uses the FMD-index, a novel compressed data structure, as the key data&nbsp;<a href="http://www.mybiosoftware.com/fermi-1-1-wgs-de-novo-assembler-based-on-the-fmd-index-for-large-genomes.html" title="Fermi 1.1 &ndash; WGS de novo Assembler based on the FMD-index for large Genomes"><br /><br /></a></li>
<li><a href="http://pasha.sourceforge.net/homepage.htm#latest" title="PASHA 1.0.10 &ndash; Parallelized Short Read Assembly">PASHA 1.0.10 &ndash; Parallelized Short Read Assembly<br /></a><a href="http://pasha.sourceforge.net/" target="_blank">PASHA</a>&nbsp;is a parallel short read assembler for large genomes using de Bruijn graphs. Taking advantage of both shared-memory multi-core CPUs and distributed-memory compute clusters, PASHA has demonstrated its potential to perform high-quality de-novo assembly of large genomes in reasonable time with modest computing resources. Our evaluation using three small real paired-end datasets shows that PASHA is able to produce better assemblies with comparable genome coverage and mis-assembly rates compared to three leading assemblers: Velvet, ABySS and SOAPdenovo. Moreover, PASHA achieves the fastest speed for all three datasets on a single CPU.<a href="http://www.mybiosoftware.com/pasha-1-0-5-parallelized-short-read-assembly.html" title="PASHA 1.0.10 &ndash; Parallelized Short Read Assembly"><br /><br /></a></li>
<li><a href="http://xgenovo.dna.bio.keio.ac.jp/" title="XGenovo &ndash; Extended Genovo Metagenomic Assembler by Incorporating Paired-End Information">XGenovo &ndash; Extended Genovo Metagenomic Assembler by Incorporating Paired-End Information<br /></a><a href="http://xgenovo.dna.bio.keio.ac.jp/" target="_blank">XGenovo</a>&nbsp;(Extended Genovo) is an extended genovo metagenomic assembler by incorporating paired-end information<a href="http://www.mybiosoftware.com/xgenovo-extended-genovo-metagenomic-assembler-by-incorporating-paired-end-information.html" title="XGenovo &ndash; Extended Genovo Metagenomic Assembler by Incorporating Paired-End Information"><br /><br /></a></li>
<li><a href="http://metavelvet.dna.bio.keio.ac.jp/" title="MetaVelvet 1.2.01 / MetaVelvet-SL &ndash; An Extension of Velvet Assembler to de novo Metagenomic Assembly / utilizing Supervised Learning">MetaVelvet 1.2.01 / MetaVelvet-SL &ndash; An Extension of Velvet Assembler to de novo Metagenomic Assembly / utilizing Supervised Learning<br /></a><a href="http://metavelvet.dna.bio.keio.ac.jp/" target="_blank">MetaVelvet</a>&nbsp;is an extension of Velvet assembler to de novo metagenome assembly from short sequence reads<a href="http://www.mybiosoftware.com/metavelvet-1-2-01-metavelvet-sl-an-extension-of-velvet-assembler-to-de-novo-metagenomic-assembly-utilizing-supervised-learning.html" title="MetaVelvet 1.2.01 / MetaVelvet-SL &ndash; An Extension of Velvet Assembler to de novo Metagenomic Assembly / utilizing Supervised Learning"><br /><br /></a></li>
<li><a href="http://www.genomic.ch/edena.php" title="Edena v3.131028 &ndash; De Novo Short Reads Assembler">Edena v3.131028 &ndash; De Novo Short Reads Assembler<br /></a><a href="http://www.genomic.ch/edena.php" target="_blank">Edena</a>&nbsp;is an assembler dedicated to process the millions of very short reads produced by the Illumina Genome Analyzer<a href="http://www.mybiosoftware.com/edena-v3-dev110920-de-novo-short-reads-assembler.html" title="Edena v3.131028 &ndash; De Novo Short Reads Assembler"><br /><br /></a></li>
<li><a href="https://github.com/gramarga/ConPADE" title="ConPADE 1.00 &ndash; Contig Ploidy and Allele Dosage Estimation">ConPADE 1.00 &ndash; Contig Ploidy and Allele Dosage Estimation<br /></a><a href="http://research.microsoft.com/en-us/downloads/62815951-4b89-47a5-9e3d-7054182dafbb/default.aspx" target="_blank">ConPADE</a>&nbsp;is a tool used to estimate contig ploidy and allele dosage in polyploid genome assemblies.<a href="http://www.mybiosoftware.com/conpade-1-00-contig-ploidy-and-allele-dosage-estimation.html" title="ConPADE 1.00 &ndash; Contig Ploidy and Allele Dosage Estimation"><br /><br /></a></li>
<li><a href="https://sourceforge.net/projects/eloper/" title="ELOPER 1.2 &ndash; Elongation of Paired-end Reads for de novo Assembly">ELOPER 1.2 &ndash; Elongation of Paired-end Reads for de novo Assembly<br /></a><a href="http://sourceforge.net/projects/eloper/" target="_blank">ELOPER</a>&nbsp;is a pre-processing tool for pair-end sequences that produces a better read library for assembly programs.<a href="http://www.mybiosoftware.com/eloper-1-2-elongation-of-paired-end-reads-for-de-novo-assembly.html" title="ELOPER 1.2 &ndash; Elongation of Paired-end Reads for de novo Assembly"><br /><br /></a></li>
<li><a href="http://www.ebi.ac.uk/~zerbino/oases/" title="Oases 0.2.08 &ndash; De novo Transcriptome Assembler for very short reads">Oases 0.2.08 &ndash; De novo Transcriptome Assembler for very short reads<br /></a><a href="http://www.ebi.ac.uk/~zerbino/oases/" target="_blank">Oases</a>&nbsp;designed to heuristically assemble RNA-seq reads in the absence of a reference genome, across a broad spectrum of expression values and in presence of alternative isoforms. It achieves this by using an array of hash lengths, a dynamic filtering of noise, a robust resolution of alternative splicing events, and the efficient merging of multiple assemblies. It was tested on human and mouse RNA-seq data and is shown to improve significantly on the transABySS and Trinity de novo&nbsp;<a href="http://www.mybiosoftware.com/oases-0-2-06-de-novo-transcriptome-assembler-short-reads.html" title="Oases 0.2.08 &ndash; De novo Transcriptome Assembler for very short reads"><br /><br /></a></li>
<li><a href="http://www.physics.rutgers.edu/~anirvans/SOPRA/" title="SOPRA 1.4.6 &ndash; Statistical Optimization of Paired Read Assembly">SOPRA 1.4.6 &ndash; Statistical Optimization of Paired Read Assembly<br /></a><a href="http://www.physics.rutgers.edu/~anirvans/SOPRA/" target="_blank">SOPRA</a>&nbsp;is an assembler for mate pair/paired-end reads from high throughput sequencing platforms, e.g. Illumina and SOLiD.<a href="http://www.mybiosoftware.com/sopra-1-4-6-statistical-optimization-paired-read-assembly.html" title="SOPRA 1.4.6 &ndash; Statistical Optimization of Paired Read Assembly"><br /><br /></a></li>
<li><a href="http://rnc.r.dendai.ac.jp/hapAssembly.html" title="hapAssembly &ndash; Haplotype Assembly from Whole-Genome Sequence Data">hapAssembly &ndash; Haplotype Assembly from Whole-Genome Sequence Data<br /></a><a href="http://rnc.r.dendai.ac.jp/hapAssembly.html" target="_blank">hapAssembly</a>&nbsp;&nbsp;beats the previous best for the important Haplotype Assembly Problem. It is&nbsp;an approach to finding optimal solutions for the haplotype assembly problem under the minimum-error-correction (MEC) model.<a href="http://www.mybiosoftware.com/hapassembly-haplotype-assembly-whole-genome-sequence-data.html" title="hapAssembly &ndash; Haplotype Assembly from Whole-Genome Sequence Data"><br /><br /></a></li>
<li><a href="https://code.google.com/archive/p/pbsim/" title="PBSIM 1.0.3 &ndash; PacBio Reads Simulator">PBSIM 1.0.3 &ndash; PacBio Reads Simulator<br /></a>PacBio sequencers produced two types of characteristic reads: CCS (short and low error rate) and CLR (long and high error rate), both of which could be useful for de novo assembly of genomes.&nbsp;<a href="https://code.google.com/p/pbsim/" target="_blank">PBSIM</a>&nbsp;simulates those PacBio reads by using either a model-based or sampling-based simulation.<a href="http://www.mybiosoftware.com/pbsim-1-0-3-pacbio-reads-simulator.html" title="PBSIM 1.0.3 &ndash; PacBio Reads Simulator"><br /><br /></a></li>
<li><a href="http://marte.ic.unicamp.br:8747/" title="SIS &ndash; Generate Draft Genome Sequence Scaffolds for Prokaryotes">SIS &ndash; Generate Draft Genome Sequence Scaffolds for Prokaryotes<br /></a><a href="http://marte.ic.unicamp.br:8747/" target="_blank">SIS</a>&nbsp;(Scaffolds from Inversion Signatures)is a new easy-to-use tool to generate contig scaffolds<a href="http://www.mybiosoftware.com/sis-generate-draft-genome-sequence-scaffolds-prokaryotes.html" title="SIS &ndash; Generate Draft Genome Sequence Scaffolds for Prokaryotes"><br /><br /></a></li>
<li><a href="https://www.cs.helsinki.fi/group/scaffold/normalizedN50/" title="NN50-calculator 0.5 &ndash; Evaluate the Correctness of Genome Assemblies">NN50-calculator 0.5 &ndash; Evaluate the Correctness of Genome Assemblies<br /></a><a href="http://www.cs.helsinki.fi/group/scaffold/normalizedN50/" target="_blank">NN50-calculator</a>&nbsp;(Normalized N50 calculator) is a tool for evaluating the correctness of genome assemblies.<a href="http://www.mybiosoftware.com/nn50-calculator-0-5-evaluate-correctness-genome-assemblies.html" title="NN50-calculator 0.5 &ndash; Evaluate the Correctness of Genome Assemblies"><br /><br /></a></li>
<li><a href="http://josephryan.github.io/baa.pl/" title="Baa.pl 0.20 &ndash; use BLAT to ASSESS an ASSEMBLY">Baa.pl 0.20 &ndash; use BLAT to ASSESS an ASSEMBLY<br /></a><a href="http://josephryan.github.io/baa.pl/" target="_blank">Baa.pl</a>&nbsp;is a simple script that parses the output of a BLAT run of a transcriptome vs. a genome assembly.<a href="http://www.mybiosoftware.com/baa-pl-0-10-blat-assess-assembly.html" title="Baa.pl 0.20 &ndash; use BLAT to ASSESS an ASSEMBLY"><br /><br /></a></li>
<li><a href="http://compbio.cs.toronto.edu/hapsembler/index.html" title="hapsembler 2.21 &ndash; Haplotype-specific Genome Assembly Toolkit">hapsembler 2.21 &ndash; Haplotype-specific Genome Assembly Toolkit<br /></a><a href="http://compbio.cs.toronto.edu/hapsembler/index.html" target="_blank">Hapsembler</a>&nbsp;is a haplotype-specific genome assembly toolkit that is designed for genomes that are rich in SNPs and other types of polymorphism. Hapsembler can be used to assemble reads from a variety of platforms including Illumina and Roche/454.<a href="http://www.mybiosoftware.com/hapsembler-2-1-haplotype-specific-genome-assembly-toolkit.html" title="hapsembler 2.21 &ndash; Haplotype-specific Genome Assembly Toolkit"><br /><br /></a></li>
<li><a href="http://alan.cs.gsu.edu/NGS/?q=content/vispa" title="ViSpA 02 &ndash; Viral Spectrum Assembler">ViSpA 02 &ndash; Viral Spectrum Assembler<br /></a><a href="http://alan.cs.gsu.edu/NGS/?q=content/vispa" target="_blank">ViSpA</a>&nbsp;(Viral Spectrum Assembling) implements a novel viral assembling and frequency estimation methods. This software uses a simple error correction, viral variants assembling based on maximum-bandwidth paths in weighted read graphs and frequency estimation via Expectation Maximization on all reads.<a href="http://www.mybiosoftware.com/vispa-01-viral-spectrum-assembler.html" title="ViSpA 02 &ndash; Viral Spectrum Assembler"><br /><br /></a></li>
<li><a href="http://www.vicbioinformatics.com/software.velvetoptimiser.shtml" title="VelvetOptimiser 2.2.5 &ndash; Automatically Optimise Velvet Assembler Parameters">VelvetOptimiser 2.2.5 &ndash; Automatically Optimise Velvet Assembler Parameters<br /></a><a href="http://www.vicbioinformatics.com/software.velvetoptimiser.shtml" target="_blank">VelvetOptimiser</a>&nbsp;is a multi-threaded Perl script for automatically optimising the three primary parameter options (K, -exp_cov, -cov_cutoff) for the Velvet de novo sequence assembler.<a href="http://www.mybiosoftware.com/velvetoptimiser-2-2-5-automatically-optimise-velvet-assembler-parameters.html" title="VelvetOptimiser 2.2.5 &ndash; Automatically Optimise Velvet Assembler Parameters"><br /><br /></a></li>
<li><a href="http://www.vicbioinformatics.com/software.assemblet.shtml" title="Assemblet 0.1 &ndash; Antigenic Variation Assembler">Assemblet 0.1 &ndash; Antigenic Variation Assembler<br /></a><a href="http://www.vicbioinformatics.com/software.assemblet.shtml" target="_blank">Assemblet</a>&nbsp;is a short read assembler for assembling antigenic variant sequences in bacteria.<a href="http://www.mybiosoftware.com/assemblet-0-1-antigenic-variation-assembler.html" title="Assemblet 0.1 &ndash; Antigenic Variation Assembler"><br /><br /></a></li>
<li><a href="http://www.vicbioinformatics.com/software.velvetk.shtml" title="VelvetK 20120606 &ndash; Find a reasonable K-mer size to Assemble Genome Reads with Velvet">VelvetK 20120606 &ndash; Find a reasonable K-mer size to Assemble Genome Reads with Velvet<br /></a><a href="http://www.vicbioinformatics.com/software.velvetk.shtml" target="_blank">VelvetK</a>&nbsp;can estimate the best k-mer size to use for your Velvet de novo assembly. It needs two inputs: the estimated genome size, and all your sequence read files. The genome size can be supplied as as a number (eg. 3.5M) or as a FASTA file of a closely related genome.<a href="http://www.mybiosoftware.com/velvetk-20120606-find-reasonable-k-mer-size-assemble-genome-reads-velvet.html" title="VelvetK 20120606 &ndash; Find a reasonable K-mer size to Assemble Genome Reads with Velvet"><br /><br /></a></li>
<li><a href="http://www.vicbioinformatics.com/software.vague.shtml" title="VAGUE 1.0.5 &ndash; Velvet Assembler Graphical User Environment">VAGUE 1.0.5 &ndash; Velvet Assembler Graphical User Environment<br /></a><a href="http://www.vicbioinformatics.com/software.vague.shtml" target="_blank">VAGUE</a>&nbsp;(Velvet Assembler Graphical Front End) is a GUI for the&nbsp;<a href="http://www.mybiosoftware.com/assembly-tools/3852">Velvet</a>&nbsp;de novo assembler.<a href="http://www.mybiosoftware.com/vague-1-0-5-velvet-assembler-graphical-user-environment.html" title="VAGUE 1.0.5 &ndash; Velvet Assembler Graphical User Environment"><br /><br /></a></li>
<li><a href="http://pritchardlab.stanford.edu/software.html" title="Transcriptome Assembler &ndash; Transcriptome Assembly used in RNA-seq of 16 Mammalian Species">Transcriptome Assembler &ndash; Transcriptome Assembly used in RNA-seq of 16 Mammalian Species<br /></a><a href="http://pritchardlab.stanford.edu/software.html" target="_blank">Transcriptome Assembler</a>&nbsp;is a software for transcriptome assembly used in RNA-seq of 16 mammalian species.<a href="http://www.mybiosoftware.com/transcriptome-assembler-transcriptome-assembly-rna-seq-16-mammalian-species.html" title="Transcriptome Assembler &ndash; Transcriptome Assembly used in RNA-seq of 16 Mammalian Species"><br /><br /></a></li>
<li><a href="http://bio.codeplex.com/wikipage?title=sequenceassembler&amp;referringTitle=sampleapps&amp;ANCHOR#sampleapps" title="BioSequenceAssembler 2.0 &ndash; Microsoft Research Sequence Assembler">BioSequenceAssembler 2.0 &ndash; Microsoft Research Sequence Assembler<br /></a><a href="http://bio.codeplex.com/wikipage?title=sequenceassembler&amp;referringTitle=sampleapps&amp;ANCHOR#sampleapps" target="_blank">BioSequenceAssembler</a>&nbsp;is intended for use by biologist and laboratory technicians who are responsible for managing next-generation genomic sequencing data for alignment, assembly, and/or BLAST identification.<a href="http://www.mybiosoftware.com/biosequenceassembler-2-0-microsoft-research-sequence-assembler.html" title="BioSequenceAssembler 2.0 &ndash; Microsoft Research Sequence Assembler"><br /><br /></a></li>
<li><a href="http://www.imperial.ac.uk/bioinformatics-data-science-group" title="BugBuilder &ndash; Microbial Genome Assembly">BugBuilder &ndash; Microbial Genome Assembly<br /></a><a href="http://www3.imperial.ac.uk/bioinfsupport/resources/software/bugbuilder" target="_blank">BugBuilder</a>&nbsp;is a pipeline for the automated assembly and annotation of microbial genomes from high-throughput sequence data. It is configurable so as not to be tied to any assembler or scaffolder, and is designed to run in a cluster environment facilitating high-throughput processing of genomes.<a href="http://www.mybiosoftware.com/bugbuilder-microbial-genome-assembly.html" title="BugBuilder &ndash; Microbial Genome Assembly"><br /></a></li>
<li><a href="http://maximuspipeline.sourceforge.net/main/">MAXIMUS 0.2 &ndash; Hybrid Reference and de novo Assembly pipeline</a><br /><a href="http://maximuspipeline.sourceforge.net/main/" target="_blank">MAXIMUS</a>&nbsp;is a genome assembly pipeline which takes the best out of multiple reference assemblies and de novo assembly. The benefits of this approach include better assembled repetitive regions, less gaps and higher accuracy for the resultant assembly.<a href="http://www.mybiosoftware.com/maximus-0-2-hybrid-reference-de-novo-assembly-pipeline.html" title="MAXIMUS 0.2 &ndash; Hybrid Reference and de novo Assembly pipeline"><br /><br /></a></li>
<li><a href="http://www.bcgsc.ca/about/pubann/the-issake-short-read-sequence-assembly-approach-for-profiling-t-cell-metagenomes" title="ISSAKE &ndash; Short Read Sequence Assembly">ISSAKE &ndash; Short Read Sequence Assembly<br /></a><a href="http://www.bcgsc.ca/about/pubann/the-issake-short-read-sequence-assembly-approach-for-profiling-t-cell-metagenomes" target="_blank">iSSAKE</a>&nbsp;(immuno-SSAKE) is a sequencing approach and assembly software for profiling T-cell metagenomes using short reads from the massively parallel sequencing platforms.<a href="http://www.mybiosoftware.com/issake-short-read-sequence-assembly.html" title="ISSAKE &ndash; Short Read Sequence Assembly"><br /><br /></a></li>
<li><a href="http://www.animalgenome.org/tools/beap/" title="IDBA / IDBA-UD 1.1.1 &ndash; De Bruijn Graph De Novo Assembler with Highly Uneven Sequencing Depth">IDBA / IDBA-UD 1.1.1 &ndash; De Bruijn Graph De Novo Assembler with Highly Uneven Sequencing Depth<br /></a><a href="http://i.cs.hku.hk/~alse/hkubrg/projects/idba/index.html" target="_blank">&nbsp;IDBA</a>&nbsp;is a practical iterative De Bruijn Graph De Novo Assembler for sequence assembly in bioinfomatics. Most assemblers based on de Bruijn graph build a de Bruijn graph with a specific k to perform the assembling task. For all of them, it is very crucial to find a specific value of k. If k is too large, there will be a lot of gap problems in the graph. If k is too small, there will a lot of branch problems. IDBA uses not only one specific k but a range of k values to build the iterative de Bruijn graph. It can keep all the information in graphs with different k values. So, it will perform better than other assemblers.<a href="http://www.mybiosoftware.com/idba-ud-1-09-de-bruijn-graph-de-novo-assembler-highly-uneven-sequencing-depth.html" title="IDBA / IDBA-UD 1.1.1 &ndash; De Bruijn Graph De Novo Assembler with Highly Uneven Sequencing Depth"><br /><br /></a></li>
<li><a href="https://code.google.com/archive/p/est2assembly/" title="est2assembly 1.13 &ndash; Assembly and Annotation of Transcriptomes for any Species">est2assembly 1.13 &ndash; Assembly and Annotation of Transcriptomes for any Species<br />The&nbsp;</a><a href="https://code.google.com/p/est2assembly/" target="_blank">est2assembly</a>&nbsp;platform is the only platform for standardising transcriptome projects: go from raw trace files to an annotated GBrowse interface driven by the Seqfeature database. It accepts both Sanger and 454 sequencing technology for a denovo assembly, annotation and data mining of EST data.<a href="http://www.mybiosoftware.com/est2assembly-1-13-assembly-annotation-transcriptomes-species.html" title="est2assembly 1.13 &ndash; Assembly and Annotation of Transcriptomes for any Species"><br /><br /></a></li>
<li><a href="https://code.google.com/archive/p/curtain/" title="Curtain 0.2.3 beta &ndash; Assembling large Genomes from Short Read Sequences">Curtain 0.2.3 beta &ndash; Assembling large Genomes from Short Read Sequences<br /></a><a href="https://code.google.com/p/curtain/" target="_blank">Curtain</a>&nbsp;is an assembler of next generation sequence. Curtain is a Java wrapper around next-generation assemblers such as Velvet, which allows the incremental introduction of read-pair information into the assembly process.<a href="http://www.mybiosoftware.com/curtain-0-2-3-beta-assembling-large-genomes-short-read-sequences.html" title="Curtain 0.2.3 beta &ndash; Assembling large Genomes from Short Read Sequences"><br /><br /></a></li>
<li><a href="http://www.comp.nus.edu.sg/~bioinfo/peasm/PE_manual.htm" title="PEAssember 1.2 &ndash; A de novo Genome Assembler">PEAssember 1.2 &ndash; A de novo Genome Assembler<br /></a><a href="http://www.comp.nus.edu.sg/~bioinfo/peasm/PE_manual.htm" target="_blank">PEAssember</a>&nbsp;is a parallel de novo genome assembler for small &ndash; mid sized genomes.<a href="http://www.mybiosoftware.com/peassember-1-2-de-novo-genome-assembler.html" title="PEAssember 1.2 &ndash; A de novo Genome Assembler"><br /><br /></a></li>
<li><a href="https://sourceforge.net/projects/contrail-bio/" title="Contrail 0.8.2 &ndash; Assembly of Large Genomes using Cloud Computing">Contrail 0.8.2 &ndash; Assembly of Large Genomes using Cloud Computing<br /></a><a href="http://contrail-bio.sourceforge.net/" target="_blank">Contrail</a>&nbsp;is a Hadoop based genome assembler for assembling large genomes in the clouds<a href="http://www.mybiosoftware.com/contrail-0-8-2-assembly-large-genomes-cloud-computing.html" title="Contrail 0.8.2 &ndash; Assembly of Large Genomes using Cloud Computing"><br /><br /></a></li>
<li><a href="http://www.mybiosoftware.com/beap-0-6-beta-blast-extension-assembly-program.html" title="BEAP 0.6 beta &ndash; Blast Extension and Assembly Program">BEAP 0.6 beta &ndash; Blast Extension and Assembly Program<br />The&nbsp;</a><a href="http://www.animalgenome.org/tools/beap/" target="_blank">BEAP</a>&nbsp;is a computer program that uses a short starting DNA fragment, often a EST or partial gene segment, as &ldquo;primer&rdquo;, to recursively blast nucleotide databases in an attempt to obtain all sequences that overlaps, directly or indirectly, with the &ldquo;primer&rdquo; therefore help to &ldquo;extend&rdquo; the length of the original sequence for constructing a &ldquo;full length&rdquo; sequence for functional analysis, or at least to obtain neighboring regions of the segment for SNP discovery and linkage disequilibrium&nbsp;<a href="http://www.mybiosoftware.com/beap-0-6-beta-blast-extension-assembly-program.html" title="BEAP 0.6 beta &ndash; Blast Extension and Assembly Program"><br /><br /></a></li>
<li><a href="http://manuals.bioinformatics.ucr.edu/home/branch" title="BRANCH 1.8.1 &ndash; boosting RNA-Seq Assemblies with Partial or related Genomic Sequences">BRANCH 1.8.1 &ndash; boosting RNA-Seq Assemblies with Partial or related Genomic Sequences<br /></a><a href="http://manuals.bioinformatics.ucr.edu/home/branch" target="_blank">BRANCH</a>&nbsp;is a software that extends de novo transfrags and identifies novel transfrags with DNA contigs or genes of close related species. BRANCH discovers novel exons first and then extends/joins fragmented de novo transfrags, so that the resulted transfrags are more complete.<a href="http://www.mybiosoftware.com/branch-1-8-1-boosting-rna-seq-assemblies-partial-related-genomic-sequences.html" title="BRANCH 1.8.1 &ndash; boosting RNA-Seq Assemblies with Partial or related Genomic Sequences"><br /><br /></a></li>
<li><a href="http://www.cbcb.umd.edu/software/quake/">Quake 0.3.5 &ndash; Detect &amp; Correct Substitution Sequencing Errors in WGS Data Sets</a><br />
<p><a href="http://www.cbcb.umd.edu/software/quake/" target="_blank">Quake</a>&nbsp;is a package to correct substitution sequencing errors in experiments with deep coverage (e.g. &gt;15X), specifically intended for Illumina sequencing reads. Quake adopts the k-mer error correction framework, first introduced by the EULER genome assembly package. Unlike EULER and similar progams, Quake utilizes a robust mixture model of erroneous and genuine k-mer distributions to determine where errors are located. Then Quake uses read quality values and learns the nucleotide to nucleotide error rates to determine what types of errors are most likely. This leads to more corrections and greater accuracy, especially with respect to avoiding mis-corrections,&nbsp;&nbsp;which create false sequence unsimilar to anything in the original genome sequence from which the read was taken.</p>
</li>
<li><a href="http://www.ebi.ac.uk/~zerbino/velvet/" title="Velvet 1.2.10 &ndash; Sequence Assembler for Very Short Reads">Velvet 1.2.10 &ndash; Sequence Assembler for Very Short Reads<br /></a><a href="http://www.ebi.ac.uk/~zerbino/velvet/" target="_blank">Velvet</a>&nbsp;is a de novo genomic assembler specially designed for short read sequencing technologies, such as Solexa or 454.Velvet currently takes in short read sequences, removes errors then produces high quality unique contigs. It then uses paired-end read and long read information, when available, to retrieve the repeated areas between contigs.<a href="http://www.mybiosoftware.com/velvet-1-1-07-sequence-assembler-short-reads.html" title="Velvet 1.2.10 &ndash; Sequence Assembler for Very Short Reads"><br /><br /></a></li>
<li><a href="http://www.complex.iastate.edu/download/Lucy2/index.html" title="Lucy 2.20 &ndash; DNA Sequence Quality &amp; Vector Trimming">Lucy 2.20 &ndash; DNA Sequence Quality &amp; Vector Trimming<br /></a><a href="http://www.complex.iastate.edu/download/Lucy2/index.html" target="_blank">Lucy</a>&nbsp;has been used for several years to clean sequence data from automated DNA sequencers prior to sequence assembly and other downstream uses. &nbsp;The quality trimming portion of lucy makes use of phred quality scores, such as those produced by many automated sequencers based on the Sanger sequencing method. &nbsp;As such, lucy&rsquo;s quality trimming may not be appropriate for sequence data produced by some of the new &ldquo;next-generation&rdquo; sequencers.<a href="http://www.mybiosoftware.com/lucy-2-19p-r8-dna-sequence-quality-vector-trimming.html" title="Lucy 2.20 &ndash; DNA Sequence Quality &amp; Vector Trimming"><br /><br /></a></li>
<li><a href="http://bioinfo.bti.cornell.edu/tool/iAssembler/">iAssembler 1.3.2 &ndash; de novo Assembly of Roche-454/Sanger Transcriptome Sequences</a><br /><a href="http://bioinfo.bti.cornell.edu/tool/iAssembler/" target="_blank">iAssembler</a>&nbsp;is a standalone package to assemble ESTs generated using Sanger and/or Roche-454 pyrosequencing technologies into contigs.<a href="http://www.mybiosoftware.com/iassembler-1-3-2-de-novo-assembly-roche-454sanger-transcriptome-sequences.html" title="iAssembler 1.3.2 &ndash; de novo Assembly of Roche-454/Sanger Transcriptome Sequences"><br /><br /></a></li>
<li><a href="http://www.broadinstitute.org/software/gaemr/" title="GAEMR 1.0.1 &ndash; Assembly Analysis Framework">GAEMR 1.0.1 &ndash; Assembly Analysis Framework<br /></a><a href="http://www.broadinstitute.org/software/gaemr/" target="_blank">GAEMR</a>&nbsp;(Genome Assembly Evaluation Metrics and Reportin) is a complete genome analysis package that helps you evaluate and report on a genome assembly&rsquo;s completeness, correctness, and contiguity.<a href="http://www.mybiosoftware.com/gaemr-1-0-1-assembly-analysis-framework.html" title="GAEMR 1.0.1 &ndash; Assembly Analysis Framework"><br /><br /></a></li>
<li><a href="https://mulcyber.toulouse.inra.fr/plugins/mediawiki/wiki/pyrocleaner/index.php/Main_Page" title="PyroCleaner 1.3 &ndash; Clean 454 Pyrosequencing Reads in order to ease the Assembly Process">PyroCleaner 1.3 &ndash; Clean 454 Pyrosequencing Reads in order to ease the Assembly Process<br />The&nbsp;</a><a href="https://mulcyber.toulouse.inra.fr/plugins/mediawiki/wiki/pyrocleaner/index.php/Main_Page" target="_blank">pyrocleaner</a>&nbsp;is intended to clean the reads included in the sff file in order to ease the assembly process. It enables filtering sequences on different criteria such as length, complexity, number of undetermined bases which has been proven to correlate with poor quality and multiple copy reads. It also enables to clean paired-ends sff files and generates on one side a sff with the validated paired-ends and on the other the sequences which can be used as shotgun reads.<a href="http://www.mybiosoftware.com/pyrocleaner-1-3-clean-454-pyrosequencing-reads-order-ease-assembly-process.html" title="PyroCleaner 1.3 &ndash; Clean 454 Pyrosequencing Reads in order to ease the Assembly Process"><br /><br /></a></li>
<li><a href="http://bioinformatics.rutgers.edu/Software/SLiQ/" title="SLiQ &ndash; Simple linear Inequalities based Mate-Pair reads Filtering and Scaffolding">SLiQ &ndash; Simple linear Inequalities based Mate-Pair reads Filtering and Scaffolding<br /></a><a href="http://bioinformatics.rutgers.edu/Software/SLiQ/" target="_blank">SLIQ&nbsp;</a>, a set of simple linear inequalities derived from the geometry of contigs on the line, can be used to predict the relative positions and orientations of contigs from individual mate pair reads and thus produce a contig digraph.<a href="http://www.mybiosoftware.com/sliq-simple-linear-inequalities-based-mate-pair-reads-filtering-scaffolding.html" title="SLiQ &ndash; Simple linear Inequalities based Mate-Pair reads Filtering and Scaffolding"><br /><br /></a></li>
<li><a href="http://bioinf.spbau.ru/en/rectangles" title="rectangles 2.0 &ndash; Rectangle Graph for Repeat Resolution in Genome Assembly">rectangles 2.0 &ndash; Rectangle Graph for Repeat Resolution in Genome Assembly<br /></a><a href="http://bioinf.spbau.ru/en/rectangles" target="_blank">rectangles</a>&nbsp;is an ultimate tool for resolving repeats in genome assemblies.<a href="http://www.mybiosoftware.com/rectangles-2-0-rectangle-graph-repeat-resolution-genome-assembly.html" title="rectangles 2.0 &ndash; Rectangle Graph for Repeat Resolution in Genome Assembly"><br /><br /></a></li>
<li><a href="http://archive.broadinstitute.org/crd/wiki/index.php/Arachne_Main_Page" title="Arachne 4.6233 &ndash; Whole-genome Shotgun Assembler">Arachne 4.6233 &ndash; Whole-genome Shotgun Assembler<br /></a><a href="http://www.broadinstitute.org/crd/wiki/index.php/Arachne_Main_Page" target="_blank">ARACHNE</a>&nbsp;is a program for assembling data from whole genome shotgun sequencing experiments. It was designed for long reads from Sanger sequencing technology, and has been used extensively to assemble many genomes, including many that are large and highly repetitive.<a href="http://www.mybiosoftware.com/arachne-3-2-whole-genome-shotgun-assembler.html" title="Arachne 4.6233 &ndash; Whole-genome Shotgun Assembler"><br /><br /></a></li>
<li><a href="http://terpconnect.umd.edu/~ALEKSEYZ/PhrapUMDV2/" title="Reconciliator 2.0 &ndash; The tool for Merging Assemblies">Reconciliator 2.0 &ndash; The tool for Merging Assemblies<br /></a><a href="http://terpconnect.umd.edu/~ALEKSEYZ/PhrapUMDV2/" target="_blank">Reconciliator</a>&nbsp;is the tool for merging assemblies.<a href="http://www.mybiosoftware.com/reconciliator-2-0-tool-merging-assemblies.html" title="Reconciliator 2.0 &ndash; The tool for Merging Assemblies"><br /><br /></a></li>
<li><a href="http://terpconnect.umd.edu/~ALEKSEYZ/PhrapUMDV2/" title="PhrapUMD 2 &ndash; Modified version of Phrap">PhrapUMD 2 &ndash; Modified version of Phrap<br /></a><a href="http://www.glue.umd.edu/~ALEKSEYZ/PhrapUMDV2" target="_blank">Phrap UMD</a>&nbsp;consists of the UMD Trimmer, UMD Overlapper and a modified version of Phrap.It is capable of assembling data downloaded directly from the NCBI Trace Archive. The pipeline runs in 3 stages: &nbsp;first the vector ends of the reads are examined and the vector is found. &nbsp;Then the reads are trimmed for vector and quality. &nbsp;After that the trimmed reads afe fed into the 5-pass UMD Overlapper that finds the overlaps, corrects the base caller errors and performs additional trimming if necessary. &nbsp;After the overlaps are produced, the trimmed and error-corrected reads and overlaps are input into the modified version of Phrap, whichonly puts the reads together if they overlap according to the list of overlaps produced by the UMD Overlapper.<a href="http://www.mybiosoftware.com/phrapumd-2-modified-version-phrap.html" title="PhrapUMD 2 &ndash; Modified version of Phrap"><br /><br /></a></li>
<li><a href="http://www.dna-dragon.com/" title="DNA Dragon 1.5.6 build1 &ndash; DNA Sequence Contig Assembler Software">DNA Dragon 1.5.6 build1 &ndash; DNA Sequence Contig Assembler Software<br /></a><a href="http://www.dna-dragon.com/" target="_blank">DNA Dragon</a>&nbsp;Contig Assembler assembles sequences, trace data (ABI, SCF, AB1), Illumina and Roche 454 flowgrams into contigs. It is a very fast and accurate DNA sequence assembly software. The DNA sequences are assembled into contigs and a direct comparision of trace date with nucleotide data is possible. It also allows for proofreading and base editing.<a href="http://www.mybiosoftware.com/dna-dragon-1-2-7-dna-sequence-contig-assembler-software.html" title="DNA Dragon 1.5.6 build1 &ndash; DNA Sequence Contig Assembler Software"><br /></a></li>
</ul>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/38238/list-of-motif-discovery-tools</guid>
	<pubDate>Tue, 20 Nov 2018 03:54:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/38238/list-of-motif-discovery-tools</link>
	<title><![CDATA[List of motif discovery tools !]]></title>
	<description><![CDATA[<div><div>In genetics, a sequence motif is a nucleotide or amino-acid sequence pattern that is widespread and has, or is conjectured to have, a biological significance. For proteins, a sequence motif is distinguished from a structural motif, a motif formed by the three-dimensional arrangement of amino acids which may not be adjacent.</div><div>&nbsp;</div><div>Following are the list of tools for motif discovery:</div><div>&nbsp;</div><div><a href="http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar/">2Dsweep -- protein annotation by secondary structure elements</a></div><p>Perform secondary structure predictions on protein sequences.</p></div><div><div><a href="http://floresta.eead.csic.es/3dfootprint/">3D-footprint -- database of DNA-binding protein structures</a></div><p>Find binding specificity information about DNA-protein complexes.</p></div><div><div><a href="http://floresta.eead.csic.es/3dfootprint/">3D-footprint: DNA-binding protein database</a></div><p>Find information about the binding specificity of DNA-binding proteins.</p></div><div><div><a href="http://3d-partner.life.nctu.edu.tw/">3D-partner -- a web server to infer interacting partners and binding models</a></div><p>Predict interacting partners and binding models.</p></div><div><div><a href="http://motif.stanford.edu/distributions/3motif/">3MOTIF -- a protein structure visualization system for conserved sequence motifs</a></div><p>Use this web-based sequence motif visualization system to display sequence motif information in its appropriate three-dimensional (3D) context.</p></div><div><div><a href="http://bioinfo.mpiz-koeln.mpg.de/afawe/">AFAWE -- Automatic functional annotation in a distributed Web Services Environment</a></div><p>Protein function prediction and annotation in an integrated environment powered by web service.</p></div><div><div><a href="http://anchor.enzim.hu/">ANCHOR -- Prediction of Protein Binding Regions in Disordered Proteins</a></div><p>Find information about protein binding.</p></div><div><div><a href="http://annie.bii.a-star.edu.sg/annie/home.do">ANNIE -- ANNotation and Interpretation Environment for Protein Sequences</a></div><p>Use to predict function from de novo protein sequences.</p></div><div><div><a href="http://bioinformatica.isa.cnr.it/ASC/">Active Sequences Collection (ASC) database -- A new tool to assign functions to protein sequences</a></div><p>Search for short active protein sequences with demonstrated biological activities.</p></div><div><div><a href="http://blocks.fhcrc.org/">Blocks -- Ungapped segments in conserved protein sequences</a></div><p>Search for ungapped segments corresponding to the most highly conserved regions of proteins.</p></div><div><div><a href="http://cast.engr.uic.edu/">CASTp -- computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues</a></div><p>Identify and measure surface accessible pockets as well as interior inaccessible cavities, for proteins and other molecules.</p></div><div><div><a href="http://www.ebi.ac.uk/thornton-srv/databases/CSA">CSA -- The Catalytic Site Atlas</a></div><p>To search for catalytic residue annotation for enzymes in the Protein Data Bank.</p></div><div><div><a href="http://www.sbg.bio.ic.ac.uk/~confunc/">ConFunc -- Conserved residue Protein Function Prediction Server</a></div><p>Predict protein function using Gene Ontology.</p></div><div><div><a href="http://consurf.tau.ac.il/">ConSurf-DB -- evolutionary conservation profiles of protein structures database</a></div><p>Automatically calculate evolutionary conservation scores of key amino acid residues and map them on protein structures.</p></div><div><div><a href="http://salilab.org/DBAli/">DBAli -- A Database of Structure Alignments</a></div><p>Mine the protein structure space.</p></div><div><div><a href="http://dilimot.embl.de/">DILIMOT -- discovery of linear motifs in proteins</a></div><p>Predict short linear motifs (3-8 residues) in a set of protein sequences.</p></div><div><div><a href="http://www.ebi.ac.uk/dasty/">Dasty2 -- an Ajax protein DAS client</a></div><p>A web client for visualizing protein sequence feature information using DAS.</p></div><div><div><a href="http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar/">DomainSweep -- protein annotation by domain analysis</a></div><p>Identify the domain architecture within a protein sequence.</p></div><div><div><a href="http://e1ds.csbb.ntu.edu.tw/">E1DS -- catalytic site prediction based on 1D signatures of concurrent conservation</a></div><p>Predict enzyme catalytic site.</p></div><div><div><a href="http://elm.eu.org/">ELM -- Eukarotic Linear Motif Resource</a></div><p>Predict functional sites in eukaryotic proteins.</p></div><div><div><a href="http://us.expasy.org/tools/#proteome">EXPASY Proteome Tools Collection</a></div><p>Use a collection of tools for protein analyses.</p></div><div><div><a href="http://us.expasy.org/tools/findmod/">EXPASY-Findmod</a></div><p>Predict potential protein post-translational modifications and find potential single amino acid substitutions in peptides.</p></div><div><div><a href="http://mbs.cbrc.jp/EzCatDB/">EzCatDB -- the Enzyme Catalytic-mechanism Database</a></div><p>Search for information related to the catalytic mechanisms of enzymes.</p></div><div><div><a href="http://bioinf.cs.ucl.ac.uk/ffpred/">FFPred -- feature-based function prediction</a></div><p>An integrated feature-based function prediction server for vertebrate proteomes.</p></div><div><div><a href="http://www.ebi.ac.uk/printsscan/">FingerPRINT Scan</a></div><p>Identify the closest matching PRINTS sequence motif fingerprints in a protein sequence.</p></div><div><div><a href="http://firedb.bioinfo.cnio.es/">FireDB -- a database of functionally important residues from proteins of known structure</a></div><p>Search for functional annotation of important sites in proteins with known structures.</p></div><div><div><a href="http://bioserv.rpbs.univ-paris-diderot.fr/cgi-bin/Frog2">Frog2 -- a FRee Online druG 3D conformation generator</a></div><p>Produce 3D conformations of small drug compounds.</p></div><div><div><a href="http://www.hgpd.jp/">HGPD -- Human Gene and Protein Database</a></div><p>A database presenting experiment-based results in human proteomics.</p></div><div><div><a href="http://hhsenser.tuebingen.mpg.de/">HHsenser -- exhaustive transitive profile search using HMMx96HMM comparison</a></div><p>Conduct exhaustive intermediate profile searches of a set of homologous protein sequences.</p></div><div><div><a href="http://loschmidt.chemi.muni.cz/hotspotwizard/">HotSpot Wizard -- Substrate Specificity Hot Spot Identification web server</a></div><p>Design protein mutations in site-directed mutagenesis.</p></div><div><div><a href="http://phylogenomics.berkeley.edu/intrepid/">INTREPID -- INformation-theoretic TREe traversal for Protein functional site IDentification</a></div><p>Use for protein functional site identification.</p></div><div><div><a href="http://www.cbs.dtu.dk/">Integrating protein annotation resources through the Distributed Annotation System</a></div><p>Annotate protein using this integrated annotation resource.</p></div><div><div><a href="http://www.ebi.ac.uk/InterProScan/">InterProScan -- protein domains identifier</a></div><p>Identify protein family (and DNA) domains, patterns, motifs, protein families, and functional sites.</p></div><div><div><a href="http://kfc.mitchell-lab.org/">KFC -- Knowledge-based FADE and Contacts</a></div><p>Interactive forecasting of protein interaction hot spots.</p></div><div><div><a href="http://biominer.bime.ntu.edu.tw/magiicpro/">MAGIIC-PRO -- detecting functional signatures by efficient discovery of long patterns in protein sequences</a></div><p>Discover long patterns in protein sequences.</p></div><div><div><a href="http://prodata.swmed.edu/malisam">MALISAM -- Manual ALIgnments for Structurally Analogous Motifs</a></div><p>Database containing pairs of structural analogs and their alignments.</p></div><div><div><a href="http://meme.nbcr.net/">MEME -- discovering and analyzing DNA and protein sequence motifs</a></div><p>Find sequence patterns in DNA and protein sequences.</p></div><div><div><a href="http://www.nii.res.in/modpropep.html">MODPROPEP -- a program for knowledge-based modeling of protein-peptide complexes</a></div><p>A web server for knowledge-based modeling of protein-peptide complexes, specifically peptides in complex with major histocompatibility complex (MHC) proteins and kinases.</p></div><div><div><a href="http://www.bioinfo.tsinghua.edu.cn/~tigerchen/memo.html">MeMo -- a web tool for prediction of protein methylation modifications</a></div><p>Predict protein methylation sites.</p></div><div><div><a href="http://caps.ncbs.res.in/MegaMotifbase/index.html">MegaMotifBase -- a database of structural motifs in protein families and superfamilies</a></div><p>Find structural segments or motifs for protein structures.</p></div><div><div><a href="http://mnm.engr.uconn.edu/MNM/SMSSearchServlet">Minimotif Miner -- a tool for investigating protein function</a></div><p>Find motifs in a protein sequence.</p></div><div><div><a href="http://umber.sbs.man.ac.uk/dbbrowser/motif3d/motif3d.html">Motif3D -- Relating protein sequence motifs to 3D structure</a></div><p>Visualize protein sequence motifs on the 3D protein structures.</p></div><div><div><a href="http://myhits.isb-sib.ch/cgi-bin/motif_scan">MotifScan</a></div><p>Find presence of any known protein motif (Prosite and Pfam) in a protein sequence.</p></div><div><div><a href="http://bioinfo3d.cs.tau.ac.il/MultiBind">MultiBind -- Multiple Alignment of Protein Binding Sites</a></div><p>Recognize spatial chemical binding patterns common to a set of protein structures.</p></div><div><div><a href="http://mendel.imp.univie.ac.at/myristate/SUPLpredictor.htm">NMT -- The MYR Predictor</a></div><p>Analyze proteins for the presence of N-terminal N-myristoylation site.</p></div><div><div><a href="http://www.cbs.dtu.dk/services/NetNGlyc/">NetNGlyc -- N-Glycosylation sites prediction tool</a></div><p>Find the presence of N-Glycosylation sites in human proteins.</p></div><div><div><a href="http://www.cbs.dtu.dk/services/NetOGlyc/">NetOGly 3.1 -- O-glycosylation sites prediction tool</a></div><p>Find the presence of O-GalNAc (mucin type) glycosylation sites in mammalian proteins.</p></div><div><div><a href="http://www.cbs.dtu.dk/services/NetPhos/">NetPhos 2.0 -- Phosphorylation sites predictions</a></div><p>Analyze eukaryotic proteins for the presence of serine, threonine and tyrosine phosphorylation sites.</p></div><div><div><a href="http://www.cbs.dtu.dk/services/NetPhosK/">NetPhosK 1.0 Server -- kinase specific eukaryotic protein phosphorylation sites prediction tool</a></div><p>Find possible kinase specific phosphorylation sites in eukaryotic proteins.</p></div><div><div><a href="http://networkin.info/search.php">NetworKIN -- a resource for exploring cellular phosphorylation networks</a></div><div>&nbsp;</div></div><div><div><a href="http://neuroproteomics.scs.uiuc.edu/neuropred.html">NeuroPred -- a tool to predict cleavage sites in neuropeptide precursors and provide the masses of the resulting peptides</a></div><p>Predict cleavage sites at basic amino acid locations in neuropeptide precursor sequences.</p></div><div><div><a href="http://www.ebi.ac.uk/patentdata/nr/">Non-Redundant Patent Sequences - Patented Sequence Database</a></div><p>Find information about patented nucleotide and protein sequences.</p></div><div><div><a href="http://www.cbs.dtu.dk/databases/OGLYCBASE/">O-GLYCBASE</a></div><p>Search for information about glycoproteins with O-linked and C-linked glycosylation sites.</p></div><div><div><a href="http://www.pandora.cs.huji.ac.il/">PANDORA -- Protein ANnotation Diagram ORiented Analysis</a></div><p>Find information about protein sequence annotations.</p></div><div><div><a href="http://sunserver.cdfd.org.in:8080/protease/PAR_3D/index.html">PAR-3D -- Protein Active site Residue - 3D structural motif</a></div><p>A server to predict protein active site residues.</p></div><div><div><a href="http://wwwmgs.bionet.nsc.ru/mgs/gnw/pdbsite/">PDBSite -- a database of the 3D structure of protein functional sites</a></div><p>Search for structural and functional information on the protein functional sites.</p></div><div><div><a href="http://wwwmgs.bionet.nsc.ru/mgs/systems/fastprot/pdbsitescan.html">PDBSiteScan -- A program for searching for active, binding and posttranslational modification sites in the 3D structures of proteins</a></div><p>Search 3D protein fragments similar in structure to known active, binding and posttranslational modification sites.</p></div><div><div><a href="http://pedant.gsf.de/">PEDANT -- Protein Extraction, Description and ANalysis Tool</a></div><p>Conduct genome wide functional and structural analysis.</p></div><div><div><a href="http://phosida.org/">PHOSIDA -- Phosphorylation site database</a></div><p>Search for phosphorylation data of any protein of interest.</p></div><div><div><a href="http://www.phosphorylation.biochem.vt.edu/">PHOSPHORYLATION SITE DATABASE</a></div><p>Search for information on prokaryotic proteins that undergo serine, threonine, or tyrosine phosphorylation.</p></div><div><div><a href="http://www.jcvi.org/pn-utility/web/smarty_wrapper/about.php">PNU -- Protein Naming Utility</a></div><p>Determine correct names for proteins.</p></div><div><div><a href="http://mbs.cbrc.jp/poodle/poodle-s.html">POODLE-S -- Predicition Of Order and Disorder by machine LEarning</a></div><p>Web application for predicting protein disorder by using physicochemical features and reduced amino acid set of a position-specific scoring matrix.</p></div><div><div><a href="http://gemdock.life.nctu.edu.tw/ppisearch/">PPISearch -- Protein-Protein Interaction Search</a></div><p>Find homologous protein-protein interactions across multiple species.</p></div><div><div><a href="http://www.ebi.ac.uk/ppsearch/">PPSearch</a></div><p>Search your query sequence against PROSITE pattern database for protein motifs.</p></div><div><div><a href="http://pridb.gdcb.iastate.edu/">PRIDB -- Protein-RNA Interface DataBase</a></div><p>Find information about protein-RNA complexes from the Protein Data Bank (PDB).</p></div><div><div><a href="http://umber.sbs.man.ac.uk/dbbrowser/PRINTS/">PRINTS and its automatic supplement, prePRINTS -- A compendium of protein fingerprints</a></div><p>Search for protein fingerprints.</p></div><div><div><a href="http://www.expasy.org/prosite/">PROSITE</a></div><p>Identify protein families and domains for a given protein sequence.</p></div><div><div><a href="http://www.imtech.res.in/raghava/prrdb/">PRRDB -- Pattern Recognition Receptor Database</a></div><p>A comprehensive database of pattern-recognition receptors and their ligands.</p></div><div><div><a href="http://www.arabidopsis.org/cgi-bin/patmatch/nph-patmatch.pl">PatMatch -- a program for finding patterns in peptide and nucleotide sequences</a></div><p>Search for short nucleotide or peptide sequences such as cis-elements in nucleotide sequences or small domains and motifs in protein sequences.</p></div><div><div><a href="http://pepcyber.umn.edu/PPEP/">PepCyber:P~PEP -- a database of human protein protein interactions mediated by phosphoprotein-binding domains</a></div><p>Database specialized in documenting human PPBD-containing proteins and PPBD-mediated interactions.</p></div><div><div><a href="http://us.expasy.org/tools/peptidecutter/">PeptideCutter -- protein cleavage sites prediction tool</a></div><p>Predicts potential protease cleavage sites and sites cleaved by chemicals in a given protein sequence.</p></div><div><div><a href="http://phobius.binf.ku.dk/">Phobius -- A combined transmembrane topology and signal peptide predictor</a></div><p>Predict combined transmembrane topology and signal peptides.</p></div><div><div><a href="http://phospho.elm.eu.org/">Phospho.ELM -- a database of phosphorylation sites</a></div><p>Search for eukaryotic phosphorylation sites.</p></div><div><div><a href="http://www.phospho3d.org/">Phospho3D -- a database of three-dimensional structures of protein phosphorylation sites</a></div><p>Search for 3D structure and functional annotation of phosphorylation sites in proteins.</p></div><div><div><a href="http://www.phosphosite.org/">PhosphoSite -- A bioinformatics resource dedicated to physiological protein phosphorylation.</a></div><p>Search the database of in vivo phosphorylation sites of human and mouse proteins</p></div><div><div><a href="http://pxgrid.med.monash.edu.au/polyq/">PolyQ -- Polyglutamine Database</a></div><p>Find information about polyglutamine (polyQ) repeats.</p></div><div><div><a href="http://www.ebi.ac.uk/pratt/">Pratt Protein motif and pattern discovery</a></div><p>Find the presence of protein motifs and patterns in an amino acid sequence.</p></div><div><div><a href="http://www.predisi.de/">PrediSi -- Prediction of Signal Peptides and their Cleavage Positions</a></div><p>Predict signal peptide sequences and their cleavage positions in bacterial and eukaryotic amino acid sequences.</p></div><div><div><a href="http://www.ebi.ac.uk/thornton-srv/databases/ProFunc/">ProFunc -- a server for predicting protein function from 3D structure</a></div><p>Predict protein functions based on known structures.</p></div><div><div><a href="http://bioinfo41.weizmann.ac.il/promate/promateus.html">ProMateus--an open research approach to protein-binding sites analysis</a></div><p>Predict the location of potential protein-protein binding sites for unbound proteins.</p></div><div><div><a href="http://www.proteus.cs.huji.ac.il/">ProTeus -- identifying signatures in protein termini</a></div><p>Identify short linear signatures in protein termini.</p></div><div><div><a href="http://genius.embnet.dkfz-heidelberg.de/menu/cgi-bin/w2h-open/w2h.open/w2h.startthis?SIMGO=w2h%2ewelcome">ProtSweep -- protein annotation by homology</a></div><p>Analyze and identify newly obtained protein sequences.</p></div><div><div><a href="http://protemot.csbb.ntu.edu.tw/">Protemot -- prediction of protein binding sites with automatically extracted geometrical templates</a></div><p>Predict protein binding sites in a protein sequence based on geometrical analysis of protein tertiary substructures.</p></div><div><div><a href="http://quasimotifinder.tau.ac.il/">QuasiMotiFinder -- protein annotation by searching for evolutionarily conserved motif-like patterns</a></div><p>Search for evolutionarily conserved motif-like patterns in protein sequences.</p></div><div><div><a href="http://bindr.gdcb.iastate.edu/RNABindR">RNABindR -- software for prediction of RNA binding residues in proteins</a></div><p>Web-based server for analyzing and predicting RNA binding sites in proteins.</p></div><div><div><a href="http://caps.ncbs.res.in/scanmot/scanmot.html">SCANMOT -- searching for similar sequences using a simultaneous scan of multiple sequence motifs</a></div><p>Search for similarities between proteins by simultaneous matching of multiple motifs.</p></div><div><div><a href="http://bioinf.fbb.msu.ru/SDPpred/">SDPpred -- A Tool for Prediction of Amino Acid Residues that Determine Differences in Functional Specificity of Homologous Proteins</a></div><p>Predict residues in protein sequences that determine the proteins' functional specificity.</p></div><div><div><a href="http://tamm.mit.edu/SDR/">SDR -- Specificity Determining Residues Database</a></div><p>Predict specificity-determining residues in protein families.</p></div><div><div><a href="http://bioware.ucd.ie/~slimdisc/">SLiMDisc -- Short, Linear Motif Discovery</a></div><p>Find shared motifs in proteins with a common attribute.</p></div><div><div><a href="http://sumosp.biocuckoo.org/">SUMOsp -- a web server for sumoylation site prediction</a></div><p>Conduct in silico sumoylation sites prediction.</p></div><div><div><a href="http://oxytricha.princeton.edu/SWAKK/">SWAKK -- a web server for detecting positive selection in proteins using a sliding window substitution rate analysis</a></div><p>Detect protein sequence section under positive evolution selection.</p></div><div><div><a href="http://www.expasy.org/tools/scanprosite/">ScanProsite</a></div><p>Search for motifs and patterns within protein sequences.</p></div><div><div><a href="http://www.expasy.org/tools/scanprosite/">ScanProsite -- detection of PROSITE signature matches and ProRule-associated functional and structural residues in proteins</a></div><p>Detect patterns, profiles and motifs in a protein sequence.</p></div><div><div><a href="http://scansite.mit.edu/">ScanSite 2.0 -- Proteome-wide prediction of cell signaling interactions using short sequence motifs</a></div><p>Search for motifs within proteins that are likely to be phosphorylated by specific protein kinases or bind to domains such as SH2 domains, 14-3-3 domains or PDZ domains.</p></div><div><div><a href="http://sepresa.bio-x.cn/">SePreSA -- SErver for the PREdiction of populations susceptible to Serious Adverse drug reaction</a></div><p>Find information about populations carrying polymorphisms within protein binding pockets that make them susceptible to serious adverse drug reaction (SADR).</p></div><div><div><a href="http://motif.genome.jp/">Sequence Motif Search</a></div><p>Search the presence of a motif in either amino acid sequence or nucleotide sequence.</p></div><div><div><a href="http://www.csbio.sjtu.edu.cn/bioinf/Signal-3L/">Signal-3L -- A 3-layer approach for predicting signal peptides</a></div><p>Predict signal peptides.</p></div><div><div><a href="http://www.cbs.dtu.dk/services/SignalP/">SignalP -- Machine learning approaches to the prediction of signal peptides, their cleavage sites, and other protein sorting signals</a></div><p>Predict signal peptides and their cleavage sites.</p></div><div><div><a href="http://us.expasy.org/tools/sulfinator/">Sulfinator -- tyrosine sulfation sites prediction tool</a></div><p>Predict the presence of tyrosine sulfation sites in protein sequences</p></div><div><div><a href="http://bioinf-services.charite.de/supersite/">SuperSite -- Ligand Binding Site Database</a></div><p>Look at protein structure from a ligand and binding site perspective.</p></div><div><div><a href="http://www.ch.embnet.org/">Swiss EMBnet node web server</a></div><p>Use a collection of bioinformatics tools at this portal site.</p></div><div><div><a href="http://bioinfo.montp.cnrs.fr/?r=t-reks">T-REKS -- identification of Tandem REpeats in sequences with a K-meanS based algorithm</a></div><p>Find information about tandem repeats in proteins that carry fundamental biological functions and are related to a number of human diseases.</p></div><div><div><a href="http://tmbeta-genome.cbrc.jp/TMFunction/">TMFunction -- The Functional Database of Membrane Proteins</a></div><p>Find information about functional residues in alpha-helical and beta-barrel membrane proteins.</p></div><div><div><a href="http://topdom.enzim.hu/">TOPDOM -- Conservatively Located Domains and Motifs in Transmembrane Proteins</a></div><p>Database of domains and motifs with conservative location in transmembrane proteins.</p></div><div><div><a href="http://motif.stanford.edu/distributions/emotif/">The EMOTIF database</a></div><p>Search for highly conserved and specific protein sequence motifs.</p></div><div><div><a href="http://treedetv2.bioinfo.cnio.es/treedet/index.html">TreeDet -- Predicting Functional Residues in Protein Sequence Alignments</a></div><p>Predict functional sites in protein sequence alignments use different methodologies.</p></div><div><div><a href="http://motif.bmi.ohio-state.edu/ChIPMotifs/">W-ChIPMotifs -- ChIP-based protein Motif discovery web server</a></div><p>Find de novo protein motifs from chromatin immunoprecipitation data.</p></div><div><div><a href="http://feature.stanford.edu/webfeature/">WebFEATURE -- an interactive web tool for identifying and visualizing functional sites on macromolecular structures</a></div><p>Scan query structures for functional sites in both proteins and nucleic acids.</p></div><div><div><a href="http://wwwmgs.bionet.nsc.ru/mgs/programs/panalyst/">WebProAnalyst -- an interactive tool for analysis of quantitative structurex96activity relationships in protein families</a></div><p>Analyze quantitative structure-activity relationship of related protein families.</p></div><div><div><a href="http://motif.stanford.edu/distributions/eblocks/">eBLOCKs -- enumerating conserved protein blocks to achieve maximal sensitivity and specificity</a></div><p>Search for ungapped alignments of highly conserved regions among a protein family or superfamily.</p></div><div><div><a href="http://ef-site.hgc.jp/eF-seek/">eF-seek -- prediction of the functional sites of proteins by searching for similar electrostatic potential and molecular surface shape</a></div><p>Predict the functional sites of proteins.</p></div><div><div><a href="http://firedb.bioinfo.cnio.es/Php/FireStar.php">firestar -- prediction of functionally important residues using structural templates and alignment reliability</a></div><p>An expert system for predicting ligand-binding residues in protein structures.</p></div><div><div><a href="http://caps.ncbs.res.in/imotdb/">iMOTdb -- a comprehensive collection of spatially interacting motifs in proteins</a></div><p>Automatically identify spatially interacting motifs among distantly related proteins sharing similar folds and possessing common ancestral lineage.</p></div>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/33306/ancestral-sequence-reconstruction-asr-or-ancestral-genesequence-reconstructionresurrection-tools-to-study-molecular-evolution</guid>
	<pubDate>Tue, 30 May 2017 04:20:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/33306/ancestral-sequence-reconstruction-asr-or-ancestral-genesequence-reconstructionresurrection-tools-to-study-molecular-evolution</link>
	<title><![CDATA[Ancestral sequence reconstruction (ASR) or ancestral gene/sequence reconstruction/resurrection tools to study molecular evolution]]></title>
	<description><![CDATA[<p><span><strong>Ancestral sequence reconstruction</strong><span>&nbsp;(</span><strong>ASR</strong><span>) &ndash; also known as&nbsp;</span><strong>ancestral gene</strong><span>/</span><strong>sequence reconstruction</strong><span>/</span><strong>resurrection</strong><span>&nbsp;&ndash; is a technique used in the study of&nbsp;</span>molecular evolution<span>. The method consists of the synthesis of an ancestral&nbsp;</span>gene<span>&nbsp;and expression of the corresponding ancestral&nbsp;</span>protein<span>.&nbsp;</span><sup id="cite_ref-thornton_1-0"><a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-thornton-1"></a></sup><span>The idea of protein 'resurrection' was suggested in 1963 by Pauling and Zuckerkandl.</span><sup id="cite_ref-2"><a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-2"></a></sup><span>&nbsp;Some early efforts were made in the eighties-nineties, led by the laboratory of&nbsp;</span>Steven A. Benner<span>, showing the potential of this technique &ndash; one that only started to be fulfilled in the post-genomic era.</span><sup id="cite_ref-3"><a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-3"></a></sup><span>&nbsp;Thanks to the improvement of algorithms and of better sequencing and synthesis techniques, the method was developed further in the early 2000s to allow the resurrection of a greater variety of and much more ancient genes.</span><sup id="cite_ref-4"><a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-4"></a></sup><span>&nbsp;Over the last decade, ancestral protein resurrection has developed as a strategy to reveal the mechanisms and dynamics of protein evolution.&nbsp;</span></span></p><p><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e4/ASR_phylogeny.png/510px-ASR_phylogeny.png" alt="image" width="610" height="435" style="border: 0px; border: 0px;"></p><p><span>Following are the list of&nbsp;</span><strong style="font-size: 12.8px;">Ancestral /sequence/ reconstruction</strong><span>&nbsp;(</span><strong style="font-size: 12.8px;">ASR</strong><span>) tools:&nbsp;</span></p><p><a href="http://www.bx.psu.edu/miller_lab/car/" target="_blank" title="To inferCars official website"><span>inferCars</span></a></p><p><span><span><span><span><span>Reconstructs contiguous regions of an ancestral genome. Given information about adjacencies between conserved segments in each modern species, our goal is to infer segment order in the ancestral genome. To get a clean and precise statement of the problem, we formalize it using graph theory. We develop an algorithm that identifies a most parsimonious scenario for the history of each individual adjacency, although the whole-genome prediction is not guaranteed to optimize traditional measures like the number of breakpoints. We introduce weights to the graph edges to model the reliability of each adjacency.</span></span></span></span></span></p><p><span><span><a href="http://paleogenomics.irmacs.sfu.ca/ANGES/" target="_blank" title="To ANGES official website">ANGES</a>:</span><a href="http://paleogenomics.irmacs.sfu.ca/ANGES/" target="_blank" title="To ANGES official website">reconstructing ANcestral GEnomeS maps</a></span></p><p><span><span><span><span><span><span>A suite of Python programs that allows reconstructing ancestral genome maps from the comparison of the organization of extant-related genomes. ANGES can reconstruct ancestral genome maps for multichromosomal linear genomes and unichromosomal circular genomes. It implements methods inspired from techniques developed to compute physical maps of extant genomes.</span></span></span></span></span></span></p><p><a href="http://virulence.molgen.mpg.de/cocos/" target="_blank" title="To Cocos official website"><span>Cocos</span></a></p><p><span><span><span><span><span><span><span>Constructs phylogenies of multi-domain proteins. With a given species tree and domain phylogenies, the procedure infers the composition of ancestral multi-domain proteins. Cocos implements and extend a suggested algorithmic approach by Behzadi and Vingron in an easy-to-use program. Such method could be applied to reconstruction of partial homologous units such as bacterial operons or protein complexes.</span></span></span></span></span></span></span></p><p><a href="https://github.com/msrosenberg/MySSP" target="_blank" title="To MySSP official website"><span>MySSP</span></a></p><p><span><span><span><span><span><span><span><span>Constructs an initial DNA sequence at the root of the tree and simulates evolution across the tree using a variety of common models of DNA evolution. MySSP is a program for the simulation of DNA sequence evolution across a phylogenetic tree. It is designed for large-scale studies, including simulation of multiple replicates and outputs sequences into NEXUS, MEGA, or FASTA formats. MySSP has a fairly simple graphical user interface (GUI) for basic use, but also has a specialized batch script interpreter to allow for more complicated or large-scale simulations.</span></span></span></span></span></span></span></span></p><p><span><span><a href="http://www.cs.cmu.edu/~ckingsf/software/parana/" target="_blank" title="To PARANA official website">PARANA</a>:&nbsp;</span><a href="http://www.cs.cmu.edu/~ckingsf/software/parana/" target="_blank" title="To PARANA official website">Parsimonious Ancestral Reconstruction And Network Analysis</a></span></p><p><span><span><span><span><span><span><span><span><span>Performs parsimony based inference of ancestral biological networks. Given multiple extant networks and phylogenetic information relating extant nodes, PARANA finds a parsimonious set of ancestral interaction events (edge gains and losses) which explain the extant networks. The framework adopted by PARANA is able to represent network evolution under models that support gene duplication and loss and independent interaction gain and loss. The method works on both directed and undirected networks and can incorporate asymmetric interaction gain and loss costs. In contrast to previous approaches, PARANA does not require knowing the relative ordering of unrelated duplication events and thus, works on phylogenetic trees even where branch lengths are not provided.</span></span></span></span></span></span></span></span></span></p><p><span><span><a href="http://www-labs.iro.umontreal.ca/~mabrouk/" target="_blank" title="To GapAdj official website">GapAdj</a>:&nbsp;</span><a href="http://www-labs.iro.umontreal.ca/~mabrouk/" target="_blank" title="To GapAdj official website">Gapped Adjacencies</a></span></p><p><span><span><span><span><span><span><span><span><span><span>A synteny-based method that is flexible enough to handle a model of evolution involving whole genome duplication events, in addition to rearrangements, gene insertions, and losses. Ancestral relationships between markers are defined in term of Gapped Adjacencies, i.e. pairs of markers separated by up to a given number of markers. It improves on a previous restricted to direct adjacencies, which revealed a high accuracy for adjacency prediction, but with the drawback of being overly conservative, i.e. of generating a large number of contiguous ancestral regions (CARs).</span></span></span></span></span></span></span></span></span></span></p><p><a href="http://ancestors.bioinfo.uqam.ca/"><span><span><span><span><span><span><span><span><span><span>ANCESTOR</span></span></span></span></span></span></span></span></span></span></a></p><p><span><span><span><span><span><span><span><span><span><span><span>A web server allowing one to easily and quickly perform the last three steps of the ancestral genome reconstruction procedure. Ancestors implements several alignment algorithms, an indel maximum likelihood solver and a context-dependent maximum likelihood substitution inference algorithm. The results presented by the server include the posterior probabilities for the last two steps of the ancestral genome reconstruction and the expected error rate of each ancestral base prediction.</span></span></span></span></span></span></span></span></span></span></span></p><p><a href="http://bioinfo.lifl.fr/procars/" target="_blank" title="To ProCARs official website"><span>ProCARs</span></a></p><p>Reconstructs ancestral gene orders as contiguous ancestral regions (CARs) with a progressive homology-based method. ProCARs runs from a phylogeny tree (without branch lengths needed) with a marked ancestor and a block file. This homology-based method is based on iteratively detecting and assembling ancestral adjacencies, while allowing some micro-rearrangements of synteny blocks at the extremities of the progressively assembled CARs. The method starts with a set of blocks as the initial set of CARs, and detects iteratively the potential ancestral adjacencies between extremities of CARs, while building up the CARs progressively by adding, at each step, new non-conflicting adjacencies that induce the less homoplasy phenomenon. The species tree is used, in some additional internal steps, to compute a score for the remaining conflicting adjacencies, and to detect other reliable adjacencies, in order to reach completely assembled ancestral genomes.</p><p><a href="http://fastml.tau.ac.il/" target="_blank" title="To FastML official website"><span>FastML</span></a></p><p>A user-friendly tool for the reconstruction of ancestral sequences. FastML implements various novel features that differentiate it from existing tools: (i) FastML uses an indel-coding method, in which each gap, possibly spanning multiples sites, is coded as binary data. FastML then reconstructs ancestral indel states assuming a continuous time Markov process. FastML provides the most likely ancestral sequences, integrating both indels and characters; (ii) FastML accounts for uncertainty in ancestral states: it provides not only the posterior probabilities for each character and indel at each sequence position, but also a sample of ancestral sequences from this posterior distribution, and a list of the k-most likely ancestral sequences; (iii) FastML implements a large array of evolutionary models, which makes it generic and applicable for nucleotide, protein and codon sequences; and (iv) a graphical representation of the results is provided, including, for example, a graphical logo of the inferred ancestral sequences.</p><p><a href="http://rth.dk/resources/maxAlike/" target="_blank" title="To maxAlike official website"><span>maxAlike</span></a></p><p>Reconstructs a genomic sequence for a specific taxon based on sequence homologs in other species. The input is a multiple sequence alignment and a phylogenetic tree that also contains the target species. For this target species, the algorithm computes nucleotide probabilities at each sequence position. Consensus sequences are then reconstructed based on a certain confidence level.</p><p><span><span><a href="http://www.geneorder.org/server.php" target="_blank" title="To MLGO official website">MLGO</a>:&nbsp;</span><a href="http://www.geneorder.org/server.php" target="_blank" title="To MLGO official website">Maximum Likelihood for Gene Order Analysis</a></span></p><p>A web tool for the reconstruction of phylogeny and/or ancestral genomes from gene-order data. MLGO was designed for analysis of large-scale genomic changes including not only rearrangements but also gene insertions, deletions and duplications. MLGO can be used to infer a phylogeny from genome rearrangement and gene order data, and can also obtain an estimation of ancestral genomes, given an input tree. MLGO takes the advantage of binary encoding on gene-order data, supports a fairly general model of genomic evolution (rearrangements plus duplications, insertions, and losses of genomic regions), and successfully accommodates itself into the framework of maximized likelihood.</p><p>Image Reference : Wiki</p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30701/harvest</guid>
	<pubDate>Tue, 31 Jan 2017 10:57:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30701/harvest</link>
	<title><![CDATA[Harvest]]></title>
	<description><![CDATA[<p>Harvest is a suite of core-genome alignment and visualization tools for quickly analyzing thousands of intraspecific microbial genomes, including variant calls, recombination detection, and phylogenetic trees.</p>
<p><a href="http://harvest.readthedocs.io/en/latest/_images/screen.png"><img src="http://harvest.readthedocs.io/en/latest/_images/screen.png" alt="_images/screen.png" style="border: 0px;"></a><span></span></p>
<p><strong>Tools</strong></p>
<ul>
<li><a href="http://harvest.readthedocs.io/en/latest/content/parsnp.html">Parsnp</a>&nbsp;- Core-genome alignment and analysis</li>
<li><a href="http://harvest.readthedocs.io/en/latest/content/gingr.html">Gingr</a>&nbsp;- Interactive visualization of alignments, trees and variants</li>
<li><a href="http://harvest.readthedocs.io/en/latest/content/harvest-tools.html">HarvestTools</a>&nbsp;- Archiving and postprocessing</li>
</ul>
<p><strong>Citation</strong></p>
<blockquote>
<div>Treangen TJ, Ondov BD, Koren S, Phillippy AM. The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biology, 15 (11), 1-15 [<a href="http://www.biomedcentral.com/content/pdf/s13059-014-0524-x.pdf">PDF</a>]</div>
</blockquote><p>Address of the bookmark: <a href="http://harvest.readthedocs.io/en/latest/index.html" rel="nofollow">http://harvest.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32465/tetra-nucleotide-analysis</guid>
	<pubDate>Thu, 04 May 2017 05:07:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32465/tetra-nucleotide-analysis</link>
	<title><![CDATA[Tetra-Nucleotide Analysis]]></title>
	<description><![CDATA[<p>A tetra-nucleotide is a fragment of DNA sequence with 4 bases (e.g. AGTC or TTGG). Pride&nbsp;<em>et al.</em>&nbsp;(2003) showed that the frequency of tetra-nucleotides in bacterial genomes contain useful, albeit weak, phylogenetic signals. Even though tetra-nucleotide analysis (TNA) utilizes the information of whole genome, it is evident that it cannot replace other alignment-based phylogenetic methods such as&nbsp;<a href="https://chunlab.wordpress.com/orthoani/">OrthoANI</a>&nbsp;or&nbsp;16S rRNA phylogeny. However, TNA can be useful for&nbsp;phylogenetic characterization when whole genome or 16S rRNA gene information is not available. For example, a partial genomic fragment obtained from a metagenome can be identified by TNA (Teeling&nbsp;<em>et al.</em>, 2004). TNA is also fast enough that it can be&nbsp;used&nbsp;as a search engine against a large genome database.</p><p>Address of the bookmark: <a href="https://chunlab.wordpress.com/tetra-nucleotide-analysis/" rel="nofollow">https://chunlab.wordpress.com/tetra-nucleotide-analysis/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</guid>
	<pubDate>Mon, 09 Jul 2018 05:20:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</link>
	<title><![CDATA[ASAR: Advanced metagenomic Sequence Analysis in R]]></title>
	<description><![CDATA[<p><span>An interactive data analysis tool for selection, aggregation and visualization of metagenomic data is presented. Functional analysis with a SEED hierarchy and pathway diagram based on KEGG orthology based upon MG-RAST annotation results is available.</span></p>
<p><span><span>To read the manual, please click the link&nbsp;</span><a href="https://askarbek-orakov.github.io/ASAR/">https://askarbek-orakov.github.io/ASAR/</a></span></p><p>Address of the bookmark: <a href="https://github.com/Askarbek-orakov/ASAR" rel="nofollow">https://github.com/Askarbek-orakov/ASAR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</guid>
	<pubDate>Wed, 29 Nov 2017 16:44:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</link>
	<title><![CDATA[Scripts for the analysis of HGT in genome sequence data.]]></title>
	<description><![CDATA[<p><span>Scripts for the analysis of HGT in genome sequence data</span></p><p>Address of the bookmark: <a href="https://github.com/reubwn/hgt" rel="nofollow">https://github.com/reubwn/hgt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40948/bio7-an-integrated-development-environment-for-ecological-modeling-scientific-image-analysis-and-statistical-analysis</guid>
	<pubDate>Fri, 07 Feb 2020 23:32:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40948/bio7-an-integrated-development-environment-for-ecological-modeling-scientific-image-analysis-and-statistical-analysis</link>
	<title><![CDATA[Bio7: an integrated development environment for ecological modeling, scientific image analysis and statistical analysis]]></title>
	<description><![CDATA[<p><span>The application Bio7 is an integrated development environment for ecological modeling, scientific image analysis and statistical analysis. The application itself is based on an RCP-Eclipse-Environment (Rich-Client-Platform) which offers a huge flexibility in configuration and extensibility because of its plug-in structure and the possibility of customization.</span></p>
<p><a href="https://bio7.org/about/">https://bio7.org/about/</a></p><p>Address of the bookmark: <a href="https://bio7.org/home-2/" rel="nofollow">https://bio7.org/home-2/</a></p>]]></description>
	<dc:creator>Nidhi Rajput</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes</guid>
	<pubDate>Thu, 09 Apr 2020 04:56:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes</link>
	<title><![CDATA[Dahak: benchmarking and containerization of tools for analysis of complex non-clinical metagenomes.]]></title>
	<description><![CDATA[<p><span>Dahak is a software suite that integrates state-of-the-art open source tools for metagenomic analyses. Tools in the dahak software suite will perform various steps in metagenomic analysis workflows including data pre-processing, metagenome assembly, taxonomic and functional classification, genome binning, and gene assignment. We aim to deliver the analytical framework as a robust and reliable containerized workflow system, which will be free from dependency, installation, and execution problems typically associated with other open-source bioinformatics solutions. This will maximize the transparency, data provenance (i.e., the process of tracing the origins of data and its movement through the workflow), and reproducibility.</span></p>
<p><span>More at&nbsp;<a href="https://dahak-metagenomics.github.io/dahak/">https://dahak-metagenomics.github.io/dahak/</a></span></p><p>Address of the bookmark: <a href="https://github.com/dahak-metagenomics/dahak" rel="nofollow">https://github.com/dahak-metagenomics/dahak</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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