<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40531?offset=410</link>
	<atom:link href="https://bioinformaticsonline.com/related/40531?offset=410" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics</guid>
	<pubDate>Thu, 29 Apr 2021 23:39:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics</link>
	<title><![CDATA[CoverM: Read coverage calculator for metagenomics]]></title>
	<description><![CDATA[<p>CoverM aims to be a configurable, easy to use and fast DNA read coverage and relative abundance calculator focused on metagenomics applications.</p>
<p>CoverM calculates coverage of genomes/MAGs&nbsp;<code>coverm genome</code>&nbsp;(<a href="https://wwood.github.io/CoverM/coverm-genome.html">help</a>) or individual contigs&nbsp;<code>coverm contig</code>&nbsp;(<a href="https://wwood.github.io/CoverM/coverm-contig.html">help</a>). Calculating coverage by read mapping, its input can either be BAM files sorted by reference, or raw reads and reference genomes in various formats.</p><p>Address of the bookmark: <a href="https://github.com/wwood/CoverM" rel="nofollow">https://github.com/wwood/CoverM</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35061/proovread-large-scale-high-accuracy-pacbio-correction-through-iterative-short-read-consensus</guid>
	<pubDate>Fri, 05 Jan 2018 04:12:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35061/proovread-large-scale-high-accuracy-pacbio-correction-through-iterative-short-read-consensus</link>
	<title><![CDATA[proovread : large-scale high-accuracy PacBio correction through iterative short read consensus]]></title>
	<description><![CDATA[<p>proovread : large-scale high-accuracy PacBio correction through iterative short read consensus</p>
<ul>
<li>outperforms PacBioToCA/LSC in terms of accuracy and contiguity/sensitivity (<a href="http://dx.doi.org/10.1093/bioinformatics/btu392">http://dx.doi.org/10.1093/bioinformatics/btu392</a>)</li>
<li>is easy to install/run/configure</li>
<li>supports various types of dat
<ul>
<li><strong>HiSeq/MiSeq&nbsp;</strong>(100-500bp)</li>
<li><strong>Unitigs</strong></li>
<li>454, ...</li>
</ul>
</li>
</ul>
<p>proovread maps high coverage data to pacbio reads (bwa mem, blasr, daligner) in multiple iterations.</p><p>Address of the bookmark: <a href="https://github.com/BioInf-Wuerzburg/proovread" rel="nofollow">https://github.com/BioInf-Wuerzburg/proovread</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39190/chipulate-a-python3-framework-to-simulate-read-counts-in-a-chip-seq-experiment</guid>
	<pubDate>Mon, 25 Mar 2019 12:46:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39190/chipulate-a-python3-framework-to-simulate-read-counts-in-a-chip-seq-experiment</link>
	<title><![CDATA[ChIPulate: A Python3 framework to simulate read counts in a ChIP-seq experiment]]></title>
	<description><![CDATA[<p><span style="color: #202020; font-size: 13px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff; float: none;">ChIP-seq simulation pipeline, ChIPulate, we assess the impact of various biological and experimental sources of variation on several outcomes of a ChIP-seq experiment, viz., the recoverability of the TF binding motif, accuracy of TF-DNA binding detection, the sensitivity of inferred TF-DNA binding strength, and number of replicates needed to confidently infer binding strength.<span> <br></span></span></p><p>Address of the bookmark: <a href="https://github.com/vishakad/chipulate" rel="nofollow">https://github.com/vishakad/chipulate</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44329/metabuli-%EB%B6%84%EB%A6%AC-improves-metagenomic-read-classification</guid>
	<pubDate>Sat, 03 Jun 2023 20:15:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44329/metabuli-%EB%B6%84%EB%A6%AC-improves-metagenomic-read-classification</link>
	<title><![CDATA[Metabuli 분리 improves metagenomic read classification]]></title>
	<description><![CDATA[<p><span>Metabuli 분리 improves metagenomic read classification through metamers, DNA-AA k-mers, to be sensitive and specific, recovering 99% and 98% of DNA or AA classifiers.</span></p>
<p>&nbsp;</p>
<p><span><span>Metabuli is metagenomic classifier that jointly analyze both DNA and amino acid (AA) sequences. DNA-based classifiers can make specific classifications, exploiting point mutations to distinguish close taxa. AA-based classifiers have higher sensitivity in detecting homology between query and reference sequences, leverageing higher conservation of AA sequences. Metabuli combines the information of both sequence types using a novel k-mer structure,&nbsp;</span><em>metamer</em><span>, to enable both specific and sensitive characterization of metagenomic samples. In addition, it can classify reads against a database of any size as long as it fits in the hard disk.</span> </span></p><p>Address of the bookmark: <a href="https://github.com/steineggerlab/Metabuli" rel="nofollow">https://github.com/steineggerlab/Metabuli</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/7986/list-of-bioinformatics-open-source-projectssoftware</guid>
	<pubDate>Tue, 21 Jan 2014 14:28:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/7986/list-of-bioinformatics-open-source-projectssoftware</link>
	<title><![CDATA[List of bioinformatics open source projects/software.]]></title>
	<description><![CDATA[<p>Open source software is software that can be freely used, changed, and shared (in modified or unmodified form) by anyone. Open source software is made by many people, and distributed under licenses that comply with the Open Source Definition.The Open Source Initiative (OSI) is a global non-profit that supports and promotes the open source movement. Followings are the OS bioinformatics projects/software :</p><p><strong>.NET Bio</strong></p><p>http://blogs.msdn.com/b/msr_er/archive/2011/10/18/microsoft-biology-foundation-evolves-into-new-toolkit-net-bio.aspx</p><p>A language-neutral bioinformatics toolkit built using the Microsoft 4.0 .NET Framework to help developers, researchers, and scientists.</p><p><strong>AMPHORA</strong> ("AutoMated Phylogenomic infeRence Application")</p><p>http://wolbachia.biology.virginia.edu/WuLab/Software.html</p><p><a href="http://en.wikipedia.org/wiki/Metagenomics" title="Metagenomics">Metagenomics</a> analysis software</p><p><strong>Anduril</strong></p><p>http://www.anduril.org/anduril/site/</p><p>Component-based <a href="http://en.wikipedia.org/wiki/Workflow" title="Workflow">workflow</a> framework for data analysis</p><p>Armadillo workflow platform</p><p>Tool for designing and executing phylogenetic workflows</p><p><strong>AutoDock</strong></p><p>http://autodock.scripps.edu/</p><p>suite of automated docking tools</p><p><strong>Biochemical Algorithms Library (BALL)</strong></p><p>http://www.ball-project.org/</p><p>C++ library and framework for molecular modeling and visualization designed for rapid prototyping</p><p><strong>Bio4j</strong></p><p>http://bio4j.com/</p><p>Bio4j is a <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">bioinformatics</a> platform and <a href="http://en.wikipedia.org/wiki/Chart" title="Chart">graph</a> based <a href="http://en.wikipedia.org/wiki/Database" title="Database">database</a> built around most data available in <a href="http://en.wikipedia.org/wiki/UniProt" title="UniProt">UniProt</a> KB(<a href="http://en.wikipedia.org/wiki/Swiss-Prot" title="Swiss-Prot">Swiss-Prot</a> + <a href="http://en.wikipedia.org/wiki/TrEMBL" title="TrEMBL">TrEMBL</a>), <a href="http://en.wikipedia.org/wiki/Gene_Ontology" title="Gene Ontology">Gene Ontology</a> (GO), <a href="http://en.wikipedia.org/w/index.php?title=UniRef&amp;action=edit&amp;redlink=1" title="UniRef (page does not exist)">UniRef</a> (50,90,100), <a href="http://en.wikipedia.org/wiki/RefSeq" title="RefSeq">RefSeq</a>, <a href="http://en.wikipedia.org/wiki/National_Center_for_Biotechnology_Information" title="National Center for Biotechnology Information">NCBI</a> taxonomy, and Expasy Enzyme DB</p><p><strong>Bioclipse</strong></p><p>www.bioclipse.net</p><p>Visual platform for <a href="http://en.wikipedia.org/wiki/Cheminformatics" title="Cheminformatics">chemo</a>- and <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">bioinformatics</a> based on the <a href="http://en.wikipedia.org/wiki/Eclipse_%28software%29" title="Eclipse (software)">Eclipse</a> Rich Client Platform (RCP).</p><p><strong>Bioconductor</strong></p><p>http://www.bioconductor.org/</p><p><a href="http://en.wikipedia.org/wiki/R_%28programming_language%29" title="R (programming language)">R (programming language)</a> language toolkit</p><p><strong>Bioinformatics Learning Tutorial (BLT)</strong></p><p>http://sourceforge.net/projects/biotutorial/</p><p>Educational <a href="http://en.wikipedia.org/wiki/Interactive_tutorials" title="Interactive tutorials">interactive tutorials</a> and 3D animations for Replication, Transcription, and Translation</p><p><strong>BioHaskell</strong></p><p>http://biohaskell.org/</p><p><a href="http://en.wikipedia.org/wiki/Haskell_%28programming_language%29" title="Haskell (programming language)">Haskell (programming language)</a></p><p><strong>BioJava</strong></p><p>http://biojava.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Java_%28programming_language%29" title="Java (programming language)">Java (programming language)</a></p><p><strong>BioMOBY</strong></p><p>http://biomoby.org/</p><p>registry of <a href="http://en.wikipedia.org/wiki/Web_services" title="Web services">web services</a></p><p><strong>BioPerl</strong></p><p>http://www.bioperl.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Perl" title="Perl">Perl</a> language toolkit</p><p><strong>BioPHP</strong></p><p>http://www.biophp.org/</p><p><a href="http://en.wikipedia.org/wiki/PHP" title="PHP">PHP</a> language toolkit</p><p><strong>Biopython</strong></p><p>http://biopython.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Python_%28programming_language%29" title="Python (programming language)">Python</a> language toolkit</p><p><strong>BioRails</strong></p><p>https://github.com/biorails</p><p>a <a href="http://en.wikipedia.org/wiki/Data_management_system" title="Data management system">data management system</a> designed to support researchers in <a href="http://en.wikipedia.org/wiki/Drug_discovery" title="Drug discovery">drug discovery</a></p><p><strong>BioRuby</strong></p><p>http://bioruby.org/</p><p><a href="http://en.wikipedia.org/wiki/Ruby_%28programming_language%29" title="Ruby (programming language)">Ruby</a> language toolkit</p><p><strong>BioSmalltalk</strong></p><p>https://code.google.com/p/biosmalltalk/</p><p><a href="http://en.wikipedia.org/wiki/Smalltalk_%28programming_language%29" title="Smalltalk (programming language)">Smalltalk</a> language toolkit</p><p><strong>BioUno</strong></p><p>http://www.biouno.org/</p><p><a href="http://en.wikipedia.org/w/index.php?title=BioUno&amp;action=edit&amp;redlink=1" title="BioUno (page does not exist)">BioUno</a> is a project that applies <a href="http://en.wikipedia.org/wiki/Continuous_Integration" title="Continuous Integration">Continuous Integration</a> tools and techniques in <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">Bioinformatics</a>. It uses <a href="http://en.wikipedia.org/wiki/Jenkins_%28software%29" title="Jenkins (software)">Jenkins</a> and its plug-in API to create <a href="http://en.wikipedia.org/wiki/Bioinformatics_workflow_management_system" title="Bioinformatics workflow management system">biology workflows</a> and manage <a href="http://en.wikipedia.org/wiki/Computer_clusters" title="Computer clusters">computer clusters</a>.</p><p><strong>caCORE</strong></p><p>&nbsp;</p><p>ontologic representation environment</p><p><strong>caArray</strong></p><p>https://cabig-stage.nci.nih.gov/community/tools/caArray</p><p>ontologic representation environment</p><p><strong>EMBOSS</strong></p><p>http://emboss.sourceforge.net/</p><p>Suite of packages for sequencing, searching, etc.</p><p><strong>Gaggle</strong></p><p>https://www.gaggle.net/</p><p>A framework for interoperability between systems biology software</p><p><strong>Galaxy</strong></p><p>http://galaxyproject.org/</p><p><a href="http://en.wikipedia.org/wiki/Scientific_workflow_system" title="Scientific workflow system">Scientific workflow</a> and <a href="http://en.wikipedia.org/wiki/Data_integration" title="Data integration">data integration</a> system</p><p><strong>GenePattern</strong></p><p>http://www.broadinstitute.org/cancer/software/genepattern/</p><p><a href="http://en.wikipedia.org/wiki/Scientific_workflow_system" title="Scientific workflow system">Scientific workflow system</a> that provides access to more than 150 genomic analysis tools</p><p><strong>GeWorkbench</strong></p><p>http://wiki.c2b2.columbia.edu/workbench/index.php/Home</p><p>Genomic <a href="http://en.wikipedia.org/wiki/Data_integration" title="Data integration">data integration</a> platform</p><p><strong>GMOD</strong></p><p>http://www.gmod.org/wiki/Main_Page</p><p>Toolkit for addressing many common challenges at biological databases.</p><p><strong>GeneProf</strong></p><p>http://www.geneprof.org/GeneProf/</p><p>A web-based, bioinformatics software suite for the analysis of functional genomics experiments, e.g. RNA-seq or ChIP-seq.</p><p><strong>GeneTalk</strong></p><p>http://www.gene-talk.de/</p><p>Tool for filtering sequence variants in <a href="http://en.wikipedia.org/wiki/Variant_Call_Format" title="Variant Call Format">VCF</a> files. Network for scientists and clinicians for expertise and knowledge exchange. Database of annotations aboute sequence variants with clinically relevant information.</p><p><strong>GenGIS</strong></p><p>http://kiwi.cs.dal.ca/GenGIS/Main_Page</p><p>Application that allows users to combine digital map data with information about biological sequences collected from the environment.</p><p><strong>GenomeSpace</strong></p><p>http://www.genomespace.org/</p><p>Centralized web application that provides data format transformations and facilitates connections with other bioinformatics tools</p><p><strong>GENtle</strong></p><p>http://directory.fsf.org/wiki/GENtle</p><p>An equivalent to the proprietary <a href="http://en.wikipedia.org/wiki/Vector_NTI" title="Vector NTI">Vector NTI</a>, a tool to analyze and edit <a href="http://en.wikipedia.org/wiki/DNA" title="DNA">DNA</a> sequence files</p><p><strong>Integrated Genome Browser</strong></p><p>http://bioviz.org/igb/</p><p><a href="http://en.wikipedia.org/wiki/Java_%28software_platform%29" title="Java (software platform)">Java</a>-based desktop <a href="http://en.wikipedia.org/wiki/Genome_browser" title="Genome browser">genome browser</a></p><p><strong>Integrative Genomics Viewer (IGV)</strong></p><p>http://www.broadinstitute.org/igv/</p><p>High-performance desktop tool for interactive visual exploration of diverse genomic data</p><p><strong>IntAct</strong></p><p>http://www.ebi.ac.uk/intact/</p><p>molecular interaction database</p><p><strong>InterMine</strong></p><p>http://intermine.github.io/intermine.org/</p><p>Extensive data warehouse system for the analysis and integration of biological datasets</p><p><strong>Java Treeview</strong></p><p>http://jtreeview.sourceforge.net/</p><p>microarray data viewer</p><p><strong>LabKey Server</strong></p><p>http://labkey.com/</p><p>platform for integrating, analyzing and sharing data</p><p><strong>OpenClinica</strong></p><p>https://www.openclinica.com/</p><p>software for capturing and managing data in clinical trials</p><p><a href="http://www.biomedcentral.com/1471-2164/13/512">PromKappa</a></p><p>http://xbioinformatics.wordpress.com/tag/promkappa/</p><p>PromKappa (Promoter analysis by Kappa) software program used for promoter pattern generation and promoter analysis.</p><p><strong>MeV: Multi-Experiment Viewer</strong></p><p>http://www.tm4.org/mev.html</p><p>a desktop application for the analysis, visualization and data-mining of large-scale genomic data</p><p><strong>PathVisio</strong></p><p>http://www.pathvisio.org/</p><p>a desktop software for drawing, analysis and visualization of biological pathways</p><p>REDCRAFT</p><p>software for determining tertiary protein structure given assigned Residual Dipolar Coupling data</p><p>SAM Tools</p><p>Data format (SAM) and accompanying tool suite, for storing large nucleotide sequence alignments</p><p><a href="http://en.wikipedia.org/wiki/Staden_Package" title="Staden Package">Staden Package</a></p><p>Sequence assembly, editing and analysis, primarily consisting of gap4, gap5 and spin.</p><p><a href="http://en.wikipedia.org/wiki/STAMP" title="STAMP">STAMP</a></p><p>Software package for analyzing metagenomic profiles that promotes &lsquo;best practices&rsquo; in choosing appropriate statistical techniques and reporting results.</p><p><a href="http://supfam.org/supraHex">supraHex</a></p><p>An open-source R/Bioconductor package for omics data analysis using a supra-hexagonal map</p><p><a href="http://en.wikipedia.org/wiki/Taverna_workbench" title="Taverna workbench">Taverna workbench</a></p><p>Tool for designing and executing workflows</p><p>TGAC Browser</p><p>Genome Browser, visualisation solutions for big data in the genomic era</p><p>T-REX WebServer</p><p>Bioinformatics and phylogenetics webserver (NJ, PhyML, RAxML, MAFFT, MUSCLE, Newick viewer, <a href="http://en.wikipedia.org/wiki/Horizontal_gene_transfer" title="Horizontal gene transfer">Horizontal gene transfer</a> detection, Reticulograms, Substitution models)</p><p><a href="http://en.wikipedia.org/wiki/UGENE" title="UGENE">UGENE</a></p><p>integrated bioinformatics tools</p><p>Visomics</p><p>bioinformatics tools for omics data</p><p>Genome Analysis Toolkit 1.0 (GATK 1.0)</p><p>a software package to analyse next-generation resequencing data</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26356/spines</guid>
	<pubDate>Tue, 09 Feb 2016 05:07:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26356/spines</link>
	<title><![CDATA[Spines]]></title>
	<description><![CDATA[<div id="content-header">
<h1>Spines</h1>
</div>
<div id="node-1301">
<div>
<div>
<p><a href="http://www.broadinstitute.org/ftp/distribution/software/spines/"><em>Spines</em></a> is a collection of software tools, developed and used by the Vertebrate Genome Biology Group at the Broad Institute. It provides basic data structures for efficient data manipulation (mostly genomic sequences, alignments, variation etc.), as well as specialized tool sets for various analyses. It also features three sequence alignment packages: <em>Satsuma,</em> a highly parallelized program for high-sensitivity, genome-wide synteny; <em>Papaya,</em> an all-purpose alignment tool for less diverged sequences; and <em>SLAP,</em> a context-sensitive local aligner for diverged sequences with large gaps.</p>
<p>Access <em>Spines</em> <a href="http://www.broadinstitute.org/ftp/distribution/software/spines/">here</a>.</p>
</div>
</div>
</div>
<p>http://www.broadinstitute.org/science/programs/genome-biology/spines</p><p>Address of the bookmark: <a href="http://www.broadinstitute.org/science/programs/genome-biology/spines" rel="nofollow">http://www.broadinstitute.org/science/programs/genome-biology/spines</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42188/tools-and-method-for-haplotype-phasing</guid>
	<pubDate>Fri, 04 Sep 2020 20:41:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42188/tools-and-method-for-haplotype-phasing</link>
	<title><![CDATA[Tools and Method for Haplotype phasing !]]></title>
	<description><![CDATA[<div>Huge amounts of genotype data are being produced with recent technological advances, both from increasingly&nbsp; comprehensive and inexpensive genome-wide SNP microarrays and from ever more accessible whole-genome and whole-exome sequencing methods. The vast amount of knowledge contained in these results, however, is best&nbsp; exploited through phased haplotypes, which classify the alleles co-located on the same chromosome. Since sequence and SNP array data normally take the form of unphased genotypes, one does not specifically observe which of the two parental chromosomes, or haplotypes, falls on a specific allele. Fortunately, new advances in both computational and laboratory methods promise improved determination of haplotype phase. Following are useful tools :</div><div>&nbsp;</div><p><strong>Arlequin:</strong>&nbsp;<a href="http://cmpg.unibe.ch/software/arlequin3/" target="_blank">http://cmpg.unibe.ch/software/arlequin3/</a></p><p><strong>BEAGLE:</strong>&nbsp;<a href="http://faculty.washington.edu/browning/beagle/beagle.html" target="_blank">http://faculty.washington.edu/browning/beagle/beagle.html</a></p><p><strong>fastPHASE:</strong>&nbsp;<a href="http://stephenslab.uchicago.edu/software.html" target="_blank">http://stephenslab.uchicago.edu/software.html</a></p><p><strong>GENEHUNTER:</strong>&nbsp;<a href="http://linkage.rockefeller.edu/soft/gh/" target="_blank">http://linkage.rockefeller.edu/soft/gh/</a></p><p><strong>The Genome Analysis Toolkit:</strong></p><p><a href="http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit" target="_blank">http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit</a></p><p><strong>IMPUTE2:</strong>&nbsp;<a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html" target="_blank">https://mathgen.stats.ox.ac.uk/impute/impute_v2.html</a></p><p><strong>MACH:</strong>&nbsp;<a href="http://www.sph.umich.edu/csg/abecasis/MACH/" target="_blank">http://www.sph.umich.edu/csg/abecasis/MACH/</a></p><p><strong>MERLIN:</strong>&nbsp;<a href="http://www.sph.umich.edu/csg/abecasis/Merlin/" target="_blank">http://www.sph.umich.edu/csg/abecasis/Merlin/</a></p><p><strong>PHASE:</strong>&nbsp;<a href="http://stephenslab.uchicago.edu/software.html" target="_blank">http://stephenslab.uchicago.edu/software.html</a></p><p><strong>PL-EM:</strong>&nbsp;<a href="http://www.people.fas.harvard.edu/~junliu/plem/" target="_blank">http://www.people.fas.harvard.edu/~junliu/plem/</a></p><p><strong>&ldquo;Read-backed phasing&rdquo; algorithm</strong>:&nbsp;<a href="http://www.broadinstitute.org/gsa/wiki/index.php/Read-backed_phasing_algorithm" target="_blank">http://www.broadinstitute.org/gsa/wiki/index.php/Read-backed_phasing_algorithm</a></p><p><strong>SHAPE-IT:</strong>&nbsp;<a href="http://www.griv.org/shapeit/" target="_blank">http://www.griv.org/shapeit/</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30355/meme-suite</guid>
	<pubDate>Fri, 23 Dec 2016 08:49:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30355/meme-suite</link>
	<title><![CDATA[MEME suite]]></title>
	<description><![CDATA[<p>Motif based sequence analysis suits&nbsp;</p>
<p>The MEME Suite allows the biologist to discover novel motifs in collections of unaligned nucleotide or protein sequences, and to perform a wide variety of other motif-based analyses.</p>
<p>The MEME Suite supports motif-based analysis of DNA, RNA and protein sequences. It provides motif discovery algorithms using both probabilistic (MEME) and discrete models (MEME), which have complementary strengths. It also allows discovery of motifs with arbitrary insertions and deletions (GLAM2). In addition to motif discovery, the MEME Suite provides tools for scanning sequences for matches to motifs (FIMO, MAST and GLAM2Scan), scanning for clusters of motifs (MCAST), comparing motifs to known motifs (Tomtom), finding preferred spacings between motifs (SpaMo), predicting the biological roles of motifs (GOMo), measuring the positional enrichment of sequences for known motifs (CentriMo), and analyzing ChIP-seq and other large datasets (MEME-ChIP).</p>
<p>The MEME Suite is comprised of a collection of tools that work together, as shown below. Not all the tools are available as webservices, so to get the full power of the MEME Suite you will need to&nbsp;<a href="http://meme-suite.org/doc/download.html">download</a>&nbsp;and&nbsp;<a href="http://meme-suite.org/doc/install.html">install</a>&nbsp;a local copy of the software. To see what has changed recently you can peruse the&nbsp;<a href="http://meme-suite.org/doc/release-notes.html">release notes</a>.</p>
<p>http://meme-suite.org/</p><p>Address of the bookmark: <a href="http://meme-suite.org/" rel="nofollow">http://meme-suite.org/</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r</guid>
	<pubDate>Fri, 06 Apr 2018 12:10:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r</link>
	<title><![CDATA[d3Network:Tools for creating D3 JavaScript network, tree, dendrogram, and Sankey graphs from R.]]></title>
	<description><![CDATA[<p><a href="http://bost.ocks.org/mike/">Mike Bostock</a><span>&rsquo;s&nbsp;</span><a href="http://d3js.org/">D3.js</a><span>&nbsp;is great for creating&nbsp;</span><a href="http://bl.ocks.org/mbostock/4062045">interactive network graphs</a><span>&nbsp;with JavaScript. The&nbsp;</span><a href="https://github.com/christophergandrud/d3Network">d3Network</a><span>&nbsp;package makes it easy to create these network graphs from&nbsp;</span><a href="http://www.r-project.org/">R</a><span>. The main idea is that you should able to take an R data frame with information about the relationships between members of a network and create full network graphs with one command.</span></p><p>Address of the bookmark: <a href="http://christophergandrud.github.io/d3Network/" rel="nofollow">http://christophergandrud.github.io/d3Network/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36395/ligand-docking-tools-and-software</guid>
	<pubDate>Wed, 25 Apr 2018 05:05:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36395/ligand-docking-tools-and-software</link>
	<title><![CDATA[Ligand Docking Tools and Software !]]></title>
	<description><![CDATA[<p>Ligand docking referred to cases where small molecule (&ldquo;ligand&rdquo;) is being docked into much larger macromolecule ("target"). The following is partial list of docking software, focusing on free (at least for academic institutes) and/or popular docking tools.&nbsp;</p><p><a href="http://autodock.scripps.edu/" target="_blank">AutoDock</a></p><p>Stochastic (GA)</p><p>Flexible ligand and partially flexible target</p><p><a href="http://www.arguslab.com/" target="_blank">ArgusLab</a></p><p>Systematic</p><p>Flexible ligandX-Score based</p><p><a href="http://dock.compbio.ucsf.edu/" target="_blank">DOCK</a></p><p>Systematic (IC)</p><p>Flexible ligandDOCK 3.5 (force field)</p><p><a href="http://www.simbiosys.ca/ehits/index.html" target="_blank">eHITS</a></p><p>Systematic (RBD of fragments followed by reconstruction)Flexible ligand and partially flexible targetHiTS_Score (empirical)</p><p><a href="http://www.biosolveit.de/" target="_blank">FlexX</a></p><p>Systematic (IC)Flexible ligandFlexX SF (empirical)Commercial</p><p><a href="http://flipdock.scripps.edu/" target="_blank">FLIPDock</a></p><p>Stochastic (GA)Flexible ligand and flexible targetAUTODOCK (empirical)</p><p><a href="http://www.eyesopen.com/products/applications/fred.html" target="_blank">FRED</a></p><p>Systematic (RBD)Flexible ligandChemScore, PLP, ScreenScore, ChemGauss (empirical/consensus)</p><p><a href="http://www.ccdc.cam.ac.uk/products/life_sciences/gold/" target="_blank">GOLD</a></p><p>Stochastic (GA)</p><p>Flexible ligand and partially flexible targetGoldScore, ChemScore (empirical), ASP (knowledge based)</p><p><a href="http://www.molsoft.com/docking.html" target="_blank">ICM</a></p><p>Stochastic (MC)</p><p>Flexible ligand and partially flexible targetICM SF (empirical)</p><p><a href="http://www.scfbio-iitd.res.in/dock/pardock.jsp" target="_blank">ParDOCK</a></p><p>Stochastic (MC)</p><p>RigidBAPPL (empirical)</p><p><em><a href="http://www.scfbio-iitd.res.in/dock/pardock.jsp" target="_blank"></a></em><a href="http://www.tcd.uni-konstanz.de/research/plants.php" target="_blank">PLANTS</a></p><p>Stochastic (ACO)Flexible ligand and partially flexible target</p><p>CHEMPLP, PLP (empirical)</p><p><a href="http://www.biopharmics.com/" target="_blank">Surflex</a></p><p>Systematic (IC/MA)Flexible ligandHammerhead based (empirical)</p><p>Point to note:</p><p>Several studies have shown that the performance of most docking tools is highly dependent on the particular characteristics of both the binding site and the ligand to be investigated, and the determination which method would be more suitable in a specific context is difficult. We encouraged you to check several docking methods to determine which one(s) work best for your system.</p><p>&nbsp;</p><p><a href="http://autodock.scripps.edu/" target="_blank"></a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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