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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36950?offset=250</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33866/perlbrew-admin-free-perl-installation-management-tool</guid>
	<pubDate>Wed, 12 Jul 2017 03:53:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33866/perlbrew-admin-free-perl-installation-management-tool</link>
	<title><![CDATA[Perlbrew: admin-free perl installation management tool.]]></title>
	<description><![CDATA[<p>perlbrew is an admin-free perl installation management tool. The latest version is 0.79, read the release note:&nbsp;<a href="https://perlbrew.pl/Release-0.79.html">Release 0.79</a>.&nbsp;</p>
<p>Copy &amp; Paste this line into your terminal:</p>
<pre><code>\curl -L https://install.perlbrew.pl | bash
</code></pre>
<p>Or, if your system does not have curl but something else:</p>
<pre><code># Linux
\wget -O - https://install.perlbrew.pl | bash

# FreeBSD
\fetch -o- https://install.perlbrew.pl | sh
</code></pre>
<p>If you prefer to install with cpan, there are two steps:</p>
<pre><code>sudo cpan App::perlbrew
perlbrew init
</code></pre>
<p>If it is installed with cpan, the perlbrew executable should be installed as&nbsp;<code>/usr/bin/perlbrew</code>&nbsp;or&nbsp;<code>/usr/local/bin/perlbrew</code>. For all users who want to use perlbrew, a prior&nbsp;<code>perlbrew init</code>&nbsp;needs to be executed.</p>
<p>The default perlbrew root directory is&nbsp;<code>~/perl5/perlbrew</code>, which can be changed by setting&nbsp;<code>PERLBREW_ROOT</code>environment variable before the installation and initialization. For more advanced installation process, please read&nbsp;<a href="http://metacpan.org/module/App::perlbrew">the perlbrew document</a>.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://perlbrew.pl/" rel="nofollow">https://perlbrew.pl/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool</guid>
	<pubDate>Fri, 01 Dec 2017 04:10:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool</link>
	<title><![CDATA[PLAST: A fast, accurate and NGS scalable bank-to-bank sequence similarity search tool]]></title>
	<description><![CDATA[<p><strong>PLAST is a fast, accurate and NGS scalable bank-to-bank sequence similarity search tool providing significant accelerations of seeds-based heuristic comparison methods, such as the Blast suite of algorithms.</strong></p>
<p><strong>Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.</strong></p>
<p>PLAST stands for&nbsp;<em>Parallel Local Sequence Alignment Search Tool&nbsp;</em>and is was&nbsp;<a href="http://www.biomedcentral.com/1471-2105/10/329" target="_blank">published in BMC Bioinformatics.</a></p>
<p>PLAST is a general purpose sequence comparison tool providing the following benefits:</p>
<ul>
<li>PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),</li>
<li>Reduces the processing time of sequences comparisons while providing highest quality results,</li>
<li>Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),</li>
<li>Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,</li>
<li>Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.</li>
</ul>
<p>https://plast.inria.fr/</p><p>Address of the bookmark: <a href="https://plast.inria.fr/" rel="nofollow">https://plast.inria.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35249/gpopsim-a-simulation-tool-for-whole-genome-genetic-data</guid>
	<pubDate>Wed, 17 Jan 2018 03:47:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35249/gpopsim-a-simulation-tool-for-whole-genome-genetic-data</link>
	<title><![CDATA[GPOPSIM: a simulation tool for whole-genome genetic data]]></title>
	<description><![CDATA[<p><span>GPOPSIM is a simulation tool for pedigree, phenotypes, and genomic data, with a variety of population and genome structures and trait genetic architectures. It provides flexible parameter settings for a wide discipline of users, especially can simulate multiple genetically correlated traits with desired genetic parameters and underlying genetic architectures.</span></p><p>Address of the bookmark: <a href="https://github.com/SCAU-AnimalGenetics/GPOPSIM" rel="nofollow">https://github.com/SCAU-AnimalGenetics/GPOPSIM</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36752/minmax-a-versatile-tool-for-calculating-and-comparing-synonymous-codon-usage-and-its-impact-on-protein-folding</guid>
	<pubDate>Thu, 24 May 2018 02:53:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36752/minmax-a-versatile-tool-for-calculating-and-comparing-synonymous-codon-usage-and-its-impact-on-protein-folding</link>
	<title><![CDATA[%MinMax: A versatile tool for calculating and comparing synonymous codon usage and its impact on protein folding.]]></title>
	<description><![CDATA[%MM calculates whether a given gene sequence encodes amino acids using the most common codons possible, the least common codons possible, or (most typically) some combination of these extremes. See our PLoS ONE paper for more details on how the %MinMax algorithm works. 

%MinMax results are averaged over an 18-codon sliding window; hence the result for "codon window = 1" is the average codon usage for codons 1-18, codon window 2 = codons 2-19, etc.<p>Address of the bookmark: <a href="http://www.codons.org/" rel="nofollow">http://www.codons.org/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</guid>
	<pubDate>Mon, 11 Jun 2018 09:44:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</link>
	<title><![CDATA[HiGlass: a tool for exploring genomic contact matrices and tracks.]]></title>
	<description><![CDATA[HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass can be run locally within a Docker container. The HiC data in the examples below is from Rao et al. (2014)

http://higlass.io/<p>Address of the bookmark: <a href="http://higlass.io/" rel="nofollow">http://higlass.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform</guid>
	<pubDate>Fri, 10 Aug 2018 13:29:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform</link>
	<title><![CDATA[FMLRC: a long-read error correction tool using the multi-string Burrows Wheeler Transform]]></title>
	<description><![CDATA[<p><span>FMLRC, or FM-index Long Read Corrector, is a tool for performing hybrid correction of long read sequencing using the BWT and FM-index of short-read sequencing data. Given a BWT of the short-read sequencing data, FMLRC will build an FM-index and use that as an implicit de Bruijn graph. Each long read is then corrected independently by identifying low frequency k-mers in the long read and replacing them with the closest matching high frequency k-mers in the implicit de Bruijn graph. In contrast to other de Bruijn graph based implementations, FMLRC is not restricted to a particular k-mer size and instead uses a two pass method with both a short "k-mer" and a longer "K-mer". This allows FMLRC to correct through low complexity regions that are computational difficult for short k-mers.</span></p><p>Address of the bookmark: <a href="https://github.com/holtjma/fmlrc" rel="nofollow">https://github.com/holtjma/fmlrc</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38449/koala-keggs-internal-annotation-tool-for-k-number-assignment-of-kegg-genes-using-ssearch-computation</guid>
	<pubDate>Wed, 12 Dec 2018 09:16:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38449/koala-keggs-internal-annotation-tool-for-k-number-assignment-of-kegg-genes-using-ssearch-computation</link>
	<title><![CDATA[KOALA: KEGG&#039;s internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation]]></title>
	<description><![CDATA[<p>KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for&nbsp;<a href="https://www.kegg.jp/kegg/ko.html">K number</a>&nbsp;assignment of KEGG GENES using SSEARCH computation. BlastKOALA and GhostKOALA assign K numbers to the user's sequence data by&nbsp;<a href="http://www.ncbi.nlm.nih.gov/blast/">BLAST</a>&nbsp;and&nbsp;<a href="http://www.bi.cs.titech.ac.jp/ghostx/">GHOSTX</a>&nbsp;searches, respectively, against a nonredundant set of KEGG GENES. Annotate Sequence in KEGG Mapper and Pathogen Checker in KEGG Pathogen are special interfaces to the BlastKOALA server and can be executed in an interactive mode. &nbsp;&nbsp; See&nbsp;<a href="https://www.kegg.jp/blastkoala/help_blastkoala.html" target="_blastkoala">Step-by-step Instructions</a>.</p>
<div>Reference: Kanehisa, M., Sato, Y., and Morishima, K. (2016) BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol. 428, 726-731. [<a href="http://www.ncbi.nlm.nih.gov/pubmed/26585406">pubmed</a>] [<a href="https://doi.org/10.1016/j.jmb.2015.11.006">pdf</a>]</div><p>Address of the bookmark: <a href="https://www.kegg.jp/blastkoala/" rel="nofollow">https://www.kegg.jp/blastkoala/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40707/vt-a-variant-tool-set-that-discovers-short-variants-from-next-generation-sequencing-data</guid>
	<pubDate>Tue, 28 Jan 2020 03:44:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40707/vt-a-variant-tool-set-that-discovers-short-variants-from-next-generation-sequencing-data</link>
	<title><![CDATA[vt: a variant tool set that discovers short variants from Next Generation Sequencing data.]]></title>
	<description><![CDATA[<p><span>vt is a variant tool set that discovers short variants from Next Generation Sequencing data.</span></p>
<p><span><a href="https://genome.sph.umich.edu/wiki/Vt">https://genome.sph.umich.edu/wiki/Vt</a></span></p>
<p><a href="https://github.com/atks/vt">https://github.com/atks/vt</a></p><p>Address of the bookmark: <a href="https://genome.sph.umich.edu/wiki/Vt" rel="nofollow">https://genome.sph.umich.edu/wiki/Vt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41442/gsp4pdb-a-web-tool-to-visualize-search-and-explore-protein-ligand-structural-patterns</guid>
	<pubDate>Sun, 15 Mar 2020 03:41:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41442/gsp4pdb-a-web-tool-to-visualize-search-and-explore-protein-ligand-structural-patterns</link>
	<title><![CDATA[GSP4PDB: a web tool to visualize, search and explore protein-ligand structural patterns]]></title>
	<description><![CDATA[<p><span><span>GSP4PDB is a user-friendly and efficient application to search and discover new patterns of protein-ligand interaction.</span></span></p>
<p><span>GSP4PDB</span><span>&nbsp;is part of the services provided by the&nbsp;</span><a href="https://structuralbio.utalca.cl/" target="_blank">Bioinformatic Group</a><span>&nbsp;of the&nbsp;</span><a href="http://www.utalca.cl/" target="_blank">University of Talca</a></p>
<p><a href="http://gdblab.com/gsp4pdb/gsp4pdb2/">http://gdblab.com/gsp4pdb/gsp4pdb2/</a></p>
<p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3352-x</p><p>Address of the bookmark: <a href="http://gdblab.com/gsp4pdb/gsp4pdb2/" rel="nofollow">http://gdblab.com/gsp4pdb/gsp4pdb2/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42139/mixtures-a-novel-tool-for-bacterial-strain-reconstruction-from-reads</guid>
	<pubDate>Fri, 21 Aug 2020 08:23:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42139/mixtures-a-novel-tool-for-bacterial-strain-reconstruction-from-reads</link>
	<title><![CDATA[mixtureS: a novel tool for bacterial strain reconstruction from reads]]></title>
	<description><![CDATA[<div>
<p>mixtureS that can de novo identify bacterial strains from shotgun reads of a clonal or metagenomic sample, without prior knowledge about the strains and their variations. Tested on 243 simulated datasets and 195 experimental datasets, mixtureS reliably identified the strains, their numbers and their abundance. Compared with three tools, mixtureS showed better performance in almost all simulated datasets and the vast majority of experimental datasets.</p>
</div>
<div>
<div>Availability</div>
<p>The source code and tool mixtureS is available at&nbsp;<a href="http://www.cs.ucf.edu/~xiaoman/mixtureS/" target="_blank">http://www.cs.ucf.edu/&tilde;xiaoman/mixtureS/</a>.</p>
</div><p>Address of the bookmark: <a href="http://www.cs.ucf.edu/~xiaoman/mixtureS/" rel="nofollow">http://www.cs.ucf.edu/~xiaoman/mixtureS/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

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