<?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/40516?offset=310</link>
	<atom:link href="https://bioinformaticsonline.com/related/40516?offset=310" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31353/concoct-clustering-contigs-with-coverage-and-composition</guid>
	<pubDate>Mon, 06 Mar 2017 04:08:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31353/concoct-clustering-contigs-with-coverage-and-composition</link>
	<title><![CDATA[CONCOCT: Clustering cONtigs with COverage and ComposiTion]]></title>
	<description><![CDATA[<p>A program for unsupervised binning of metagenomic contigs by using nucleotide composition, coverage data in multiple samples and linkage data from paired end reads.</p>
<p>Warning! This software is to be considered under development. Functionality and the user interface may still change significantly from one version to another. If you want to use this software, please stay up to date with the list of known issues:<a href="https://github.com/BinPro/CONCOCT/issues">https://github.com/BinPro/CONCOCT/issues</a></p><p>Address of the bookmark: <a href="https://github.com/BinPro/CONCOCT" rel="nofollow">https://github.com/BinPro/CONCOCT</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31382/seqmule-automated-human-exomegenome-variants-detection</guid>
	<pubDate>Tue, 07 Mar 2017 10:12:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31382/seqmule-automated-human-exomegenome-variants-detection</link>
	<title><![CDATA[SeqMule: Automated human exome/genome variants detection]]></title>
	<description><![CDATA[<p><span>SeqMule takes single-end or paird-end FASTQ or BAM files, generates a script consisting of more than 10 popular alignment, analysis tools and runs the script line by line. Users can change the pipeline or fine-tune the parameters by modifying its configuration file. SeqMule also has some built-in functions, such as pooling consensus calls from various callers, plotting a Venn diagram showing intersection among different callers, and downloading databases. SeqMule can be used for both Mendelian disease study and cancer genome study.</span></p><p>Address of the bookmark: <a href="http://seqmule.openbioinformatics.org/en/latest/" rel="nofollow">http://seqmule.openbioinformatics.org/en/latest/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</guid>
	<pubDate>Fri, 05 May 2017 06:11:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</link>
	<title><![CDATA[Bacterial genome assembly !!]]></title>
	<description><![CDATA[<p>This tutorial will serve as an example of how to use free and open-source genome assembly and secondary scaffolding tools to generate high quality assemblies of&nbsp;bacterial sequence data. The bacterial sample used in this tutorial will be referred&nbsp;to simply&nbsp;as &ldquo;Species&rdquo; since it is&nbsp;live data. This data is paired-end data, meaning that there are forward and reverse reads, which we will designate as Sample_R1.fastq and Sample_R2.fastq, respectively.</p>
<p>https://github.com/jennomics/WorkflowPaper/blob/master/Genome%20Assembly%20and%20Annotation.md</p><p>Address of the bookmark: <a href="http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/" rel="nofollow">http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32730/ncbi-prokaryotic-genome-annotation-pipeline</guid>
	<pubDate>Tue, 16 May 2017 08:56:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32730/ncbi-prokaryotic-genome-annotation-pipeline</link>
	<title><![CDATA[NCBI Prokaryotic Genome Annotation Pipeline]]></title>
	<description><![CDATA[<p>NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).</p>
<p>Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.</p>
<p>NCBI has developed an automatic prokaryotic genome annotation pipeline that combines&nbsp;<em>ab initio</em>&nbsp;gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP;&nbsp;<a href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=pubmed&amp;dopt=Abstract&amp;list_uids=18416670">see Pubmed Article</a>) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume. You can find a more detailed description of the new version of&nbsp;the pipeline in&nbsp;<a href="https://www.ncbi.nlm.nih.gov/books/NBK174280/">NCBI Handbook chapter</a>. NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.</p>
<p>https://www.ncbi.nlm.nih.gov/genome/annotation_prok/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/genome/annotation_prok/" rel="nofollow">https://www.ncbi.nlm.nih.gov/genome/annotation_prok/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35540/hinge-long-read-assembly-achieves-optimal-repeat-resolution</guid>
	<pubDate>Wed, 07 Feb 2018 09:40:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35540/hinge-long-read-assembly-achieves-optimal-repeat-resolution</link>
	<title><![CDATA[HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution]]></title>
	<description><![CDATA[<p>Software accompanying "HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution"</p>
<ul>
<li>
<p>Preprint:&nbsp;<a href="http://biorxiv.org/content/early/2016/08/01/062117">http://biorxiv.org/content/early/2016/08/01/062117</a></p>
</li>
<li>
<p>Paper:&nbsp;<a href="http://genome.cshlp.org/content/27/5/747.full">http://genome.cshlp.org/content/27/5/747.full</a></p>
</li>
<li>
<p>An ipython notebook to reproduce results in the paper can be found in this&nbsp;<a href="https://github.com/govinda-kamath/HINGE-analyses">repository</a>.</p>
</li>
</ul>
<p>HINGE is an OLC(Overlap-Layout-Consensus) assembler. The idea of the pipeline is shown below.</p>
<p><a href="https://github.com/HingeAssembler/HINGE/blob/master/misc/High_level_overview.png" target="_blank"><img src="https://github.com/HingeAssembler/HINGE/raw/master/misc/High_level_overview.png" alt="image" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/HingeAssembler/HINGE" rel="nofollow">https://github.com/HingeAssembler/HINGE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36897/gmcloser-closing-gaps-in-assemblies-accurately-with-a-likelihood-based-selection-of-contig-or-long-read-alignments</guid>
	<pubDate>Mon, 11 Jun 2018 05:43:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36897/gmcloser-closing-gaps-in-assemblies-accurately-with-a-likelihood-based-selection-of-contig-or-long-read-alignments</link>
	<title><![CDATA[GMcloser: closing gaps in assemblies accurately with a likelihood-based selection of contig or long-read alignments]]></title>
	<description><![CDATA[GMcloser uses likelihood-based classifiers calculated from the alignment statistics between scaffolds, contigs and paired-end reads to correctly assign contigs or long reads to gap regions of scaffolds, thereby achieving accurate and efficient gap closure. We demonstrate with sequencing data from various organisms that the gap-closing accuracy of GMcloser is 3–100-fold higher than those of other available tools, with similar efficiency.

https://academic.oup.com/bioinformatics/article/31/23/3733/209212<p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/31/23/3733/209212" rel="nofollow">https://academic.oup.com/bioinformatics/article/31/23/3733/209212</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38316/simba-a-genome-assembly-project-management-system</guid>
	<pubDate>Thu, 29 Nov 2018 08:52:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38316/simba-a-genome-assembly-project-management-system</link>
	<title><![CDATA[SIMBA: a Genome Assembly Project Management System]]></title>
	<description><![CDATA[<p><span>SIMBA</span><span>, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS) platforms quickly, easily and effectively. SIMBA also is open source tool, i.e., can be freely downloaded, shared and modified.</span></p><p>Address of the bookmark: <a href="http://ufmg-simba.sourceforge.net/" rel="nofollow">http://ufmg-simba.sourceforge.net/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42626/spades-team-announce-new-version-spades-v315</guid>
	<pubDate>Fri, 15 Jan 2021 10:24:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42626/spades-team-announce-new-version-spades-v315</link>
	<title><![CDATA[SPADes team announce new version SPADes v3.15]]></title>
	<description><![CDATA[<p>New SPAdes 3.15.0.0. announced by the SPADes team This release includes such new features as:&nbsp;<br />- CoronaSPAdes pipeline for the assembly of transcriptomic and metatranscriptomic data of full-length coronaviridae genomes;&nbsp;<br />- Meta-Viral and RNA-Viral pipelines for metagenomic and metatranscriptomic data defining viral genomes;&nbsp;<br />-New trusted contiguous use algorithm;&nbsp;<br />-Switched to the memory allocator mimalloc;&nbsp;<br />- PlasmidSPAdes and bgcSPAdes are now provided as an input assembly graph;&nbsp;<br />- Important improvements and corrections to the metaplasmid pipeline;&nbsp;<br />- Multiple performance improvements in procedures for simplification and repeat resolving.&nbsp;<br />Please, consider updating.</p><p>Check out more at&nbsp;https://cab.spbu.ru/software/spades/</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43315/genome-assembly-workshop-2020</guid>
	<pubDate>Wed, 25 Aug 2021 04:30:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43315/genome-assembly-workshop-2020</link>
	<title><![CDATA[Genome Assembly Workshop 2020]]></title>
	<description><![CDATA[<p><span>Our team offers custom bioinformatics services to academic and private organizations. We have a strong academic background with a focus on cutting edge, open source software. We replicate standard analysis pipelines (best practices) when appropriate, and/or develop novel applications and pipelines when needed, however we always emphasize biological interpretation of the data.</span></p>
<p><span>More at&nbsp;https://ucdavis-bioinformatics-training.github.io/</span></p><p>Address of the bookmark: <a href="https://ucdavis-bioinformatics-training.github.io/2020-Genome_Assembly_Workshop/snakemake/snakemake_intro" rel="nofollow">https://ucdavis-bioinformatics-training.github.io/2020-Genome_Assembly_Workshop/snakemake/snakemake_intro</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</guid>
	<pubDate>Wed, 08 Mar 2023 01:39:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</link>
	<title><![CDATA[ALE: Assembly Likelihood Estimator]]></title>
	<description><![CDATA[<p>Just import the assembly, bam and ALE scores. You can convert the .ale file to a set of .wig files with ale2wiggle.py and IGV can read those directly.&nbsp; Depending on your genome size you may want to convert the .wig files to the BigWig format.</p><p>Address of the bookmark: <a href="https://github.com/sc932/ALE" rel="nofollow">https://github.com/sc932/ALE</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

</channel>
</rss>