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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44655?offset=40</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/27311/release-notes-for-genome-workbench-2105</guid>
	<pubDate>Thu, 12 May 2016 13:49:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/27311/release-notes-for-genome-workbench-2105</link>
	<title><![CDATA[Release Notes for Genome Workbench 2.10.5]]></title>
	<description><![CDATA[<p>New Features in latest release</p><ul>
<li>New ProSplign tool integrated with Genome Workbench (<a href="https://www.ncbi.nlm.nih.gov/tools/gbench/tutorial13">Tutorial</a>,&nbsp;<a href="https://www.youtube.com/watch?v=V9UqKJprzAg&amp;feature=youtu.be" target="_blank">Video</a>)</li>
<li>New export function for BAM/cSRA coverage graphs (<a href="https://www.ncbi.nlm.nih.gov/tools/gbench/tutorial14">Tutorial</a>)</li>
<li>New export function for alignments GFF3 format ((<a href="https://www.ncbi.nlm.nih.gov/tools/gbench/tutorial15">Tutorial</a>))</li>
<li>Tree View: implemented new export mode based on selections (tutorial coming)</li>
<li>Tree View: added support for&nbsp;<a href="https://www.ncbi.nlm.nih.gov/tools/gbench/tutorial3/#distance_based_circular_trees">distance based circular trees</a></li>
<li>Tree View: new rooting mode (Midpoint Root) results in more balanced trees (<a href="https://www.ncbi.nlm.nih.gov/tools/gbench/tutorial3#reroot_tree">Tutorial</a>)</li>
<li>Tree View: added possibility to right-click on an edge between two nodes and "Place Root at Middle of Branch" &ndash; to re-root at mid-branch (<a href="https://www.ncbi.nlm.nih.gov/tools/gbench/tutorial3#reroot_tree">Tutorial</a>)</li>
</ul>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27432/gkno</guid>
	<pubDate>Fri, 20 May 2016 18:56:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27432/gkno</link>
	<title><![CDATA[GKNO]]></title>
	<description><![CDATA[<p><span>gkno opens the world of complex bioinformatic analysis to people of all level of computational expertise. This site contains documentation, tutorials and information on all the tools that comprise gkno.</span></p>
<p><span>http://gkno.me/how-to/install.html</span></p>
<p><span>http://gkno.me/software.html</span></p><p>Address of the bookmark: <a href="http://gkno.me/" rel="nofollow">http://gkno.me/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27839/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads-such-those-produced-by-pacific-biosciences-sequencing-machines</guid>
	<pubDate>Wed, 15 Jun 2016 17:18:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27839/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads-such-those-produced-by-pacific-biosciences-sequencing-machines</link>
	<title><![CDATA[LoRMA: a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines]]></title>
	<description><![CDATA[<p>LoRMA is a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines.</p>
<p>Publication:</p>
<ul>
<li>L. Salmela, R. Walve, E. Rivals, and E. Ukkonen: Accurate selfcorrection of errors in long reads using de Bruijn graphs. Accepted to RECOMB-Seq 2016.</li>
</ul>
<p>Download:</p>
<ul>
<li><a href="https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/LoRMA-0.3.tar.gz">LoRMA 0.3 source files</a></li>
<li><a href="https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/README.txt">README</a></li>
</ul><p>Address of the bookmark: <a href="https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/" rel="nofollow">https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30680/easybuild</guid>
	<pubDate>Fri, 27 Jan 2017 16:00:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30680/easybuild</link>
	<title><![CDATA[EasyBuild]]></title>
	<description><![CDATA[<p><a href="https://github.com/hpcugent/easybuild">EasyBuild</a><span>&nbsp;is a software build and installation framework that allows you to manage (scientific) software on High Performance Computing (HPC) systems in an efficient way.</span><br><span>A full list of supported software packages is available&nbsp;</span><a href="http://easybuild.readthedocs.io/en/latest/version-specific/Supported_software.html">here</a><span>.</span></p><p>Address of the bookmark: <a href="https://hpcugent.github.io/easybuild/" rel="nofollow">https://hpcugent.github.io/easybuild/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</guid>
	<pubDate>Tue, 23 May 2017 05:28:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</link>
	<title><![CDATA[SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology]]></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>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1344-7</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>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44571/panacus-a-counting-tool-for-pangenome-graphs</guid>
	<pubDate>Fri, 14 Jun 2024 14:42:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44571/panacus-a-counting-tool-for-pangenome-graphs</link>
	<title><![CDATA[Panacus : A Counting Tool for Pangenome Graphs]]></title>
	<description><![CDATA[<p dir="auto"><code>panacus</code>&nbsp;is a tool for calculating statistics for&nbsp;<a href="https://github.com/GFA-spec/GFA-spec/blob/master/GFA1.md">GFA</a>&nbsp;files. It supports GFA files with&nbsp;<code>P</code>&nbsp;and&nbsp;<code>W</code>&nbsp;lines, but requires that the graph is&nbsp;<code>blunt</code>, i.e., nodes do not overlap and consequently, each link (<code>L</code>) points from the end of one segment (<code>S</code>) to the start of another.</p>
<p dir="auto"><code>panacus</code>&nbsp;supports the following calculations:</p>
<ul dir="auto">
<li>coverage histogram</li>
<li>pangenome growth statistics</li>
<li>path-/group-resolved coverage table</li>
</ul><p>Address of the bookmark: <a href="https://github.com/marschall-lab/panacus" rel="nofollow">https://github.com/marschall-lab/panacus</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45249/from-dna-chaos-to-a-clear-microbial-story</guid>
	<pubDate>Fri, 21 Aug 2026 11:22:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45249/from-dna-chaos-to-a-clear-microbial-story</link>
	<title><![CDATA[From DNA Chaos to a Clear Microbial Story]]></title>
	<description><![CDATA[<p>Imagine opening a metagenomic dataset and finding millions of DNA fragments, each carrying a tiny piece of information about the microbial world inside a sample. The challenge is not generating the data &mdash; it is turning that data into a meaningful story.</p><p>This is where MeTAline comes in.</p><p>MeTAline is a reproducible workflow designed to simplify shotgun metagenomic analysis. It brings together important steps such as quality control, host-DNA removal, taxonomic profiling and functional analysis, using tools including Kraken2, MetaPhlAn4 and HUMAnN.</p><p>What makes it especially useful is its ability to handle large datasets while keeping analyses organized and reproducible. Built with Snakemake and supporting containerized environments, MeTAline can also be used on high-performance computing systems.</p><p>In simple terms, MeTAline helps researchers move from millions of confusing DNA fragments to a clearer picture of who is there, what they might be doing, and what the data could mean.</p><p>Sometimes, the biggest challenge in science isn't collecting more data &mdash; it's finding the story hidden inside it.</p><p>Read more at&nbsp;https://academic.oup.com/nargab/article/7/4/lqaf158/8340158?login=false</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42963/davi-deep-learning-based-tool-for-alignment-and-single-nucleotide-variant-identification</guid>
	<pubDate>Tue, 16 Mar 2021 05:41:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42963/davi-deep-learning-based-tool-for-alignment-and-single-nucleotide-variant-identification</link>
	<title><![CDATA[DAVI: Deep learning-based tool for alignment and single nucleotide variant identification]]></title>
	<description><![CDATA[<p>DAVI consists of models for both global and local alignment and for variant calling. We have evaluated the performance of DAVI against existing state-of-the-art tool sets and found that its accuracy and performance is comparable to existing tools used for bench-marking. We further demonstrate that while existing tools are based on data generated from a specific sequencing technology, the models proposed in DAVI are generic and can be used across different NGS technologies as well as across different species</p>
<p>https://iopscience.iop.org/article/10.1088/2632-2153/ab7e19/pdf</p><p>Address of the bookmark: <a href="https://github.com/gguptaiitd/NEAT" rel="nofollow">https://github.com/gguptaiitd/NEAT</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34380/chsminer-a-gui-tool-to-identify-chromosomal-homologous-segments</guid>
	<pubDate>Sat, 18 Nov 2017 16:55:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34380/chsminer-a-gui-tool-to-identify-chromosomal-homologous-segments</link>
	<title><![CDATA[CHSMiner: a GUI tool to identify chromosomal homologous segments]]></title>
	<description><![CDATA[<div id="ASec1">
<h3>Background</h3>
<p>The identification of chromosomal homologous segments (CHS) within and between genomes is essential for comparative genomics. Various processes including insertion/deletion and inversion could cause the degeneration of CHSs.</p>
</div>
<div id="ASec2">
<h3>Results</h3>
<p>Here we present a Java software CHSMiner that detects CHSs based on shared gene content alone. It implements fast greedy search algorithm and rigorous statistical validation, and its friendly graphical interface allows interactive visualization of the results. We tested the software on both simulated and biological realistic data and compared its performance with similar existing software and data source.</p>
</div>
<div id="ASec3">
<h3>Conclusion</h3>
<p>CHSMiner is characterized by its integrated workflow, fast speed and convenient usage. It will be useful for both experimentalists and bioinformaticians interested in the structure and evolution of genomes.</p>
<p>&nbsp;</p>
<p>https://github.com/zhenwang100/CHSMiner</p>
</div><p>Address of the bookmark: <a href="https://almob.biomedcentral.com/articles/10.1186/1748-7188-4-2" rel="nofollow">https://almob.biomedcentral.com/articles/10.1186/1748-7188-4-2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</guid>
	<pubDate>Fri, 08 Dec 2017 16:26:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</link>
	<title><![CDATA[jobTree based python wrapper to run the genome simulation tool suite Evolver]]></title>
	<description><![CDATA[<p><span>evolverSimControl</span><span>&nbsp;(</span><span>eSC</span><span>) can be used to simulate multi-chromosome genome evolution on an arbitrary phylogeny (</span><a href="http://evolution.genetics.washington.edu/phylip/newicktree.html">Newick format</a><span>). In addition to simply running evolver,&nbsp;</span><span>eSC</span><span>&nbsp;also automatically creates statistical summaries of the simulation as it runs including text and image files. Also included are convenience scripts to: check on a running simulation and see detailed status and logging information; extract fasta sequence files from the leaf nodes of a completed simulation; extract pairwise multiple alignment files (</span><a href="http://genome.ucsc.edu/FAQ/FAQformat.html#format5">.maf</a><span>) from leaf and branch nodes from a completed simulation and with the help of&nbsp;</span><a href="https://github.com/dentearl/mafTools/">mafJoin</a><span>, join them together into a single maf covering the entire simulation.</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/evolverSimControl" rel="nofollow">https://github.com/dentearl/evolverSimControl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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