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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38561?offset=90</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34543/acana-an-accurate-and-consistent-alignment-tool-for-dna-sequences</guid>
	<pubDate>Wed, 06 Dec 2017 09:45:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34543/acana-an-accurate-and-consistent-alignment-tool-for-dna-sequences</link>
	<title><![CDATA[ACANA: An accurate and consistent alignment tool for DNA sequences]]></title>
	<description><![CDATA[<p><span>ACANA is an accurate and consistent alignment tool for DNA sequences. ACANA is specifically designed for aligning sequences that share only some moderately conserved regions and/or have a high frequency of long insertions or deletions. It attempts to combine the best of local and global alignments algorithms in searching for evolutionarily related regions of sequences in order to achieve the best alignment. ACANA is also robust to the small changes of alignment parameters, particularly the gap extension score. As an accurate alignment tool, ACANA is particularly useful in comparative sequence analysis for identifying conserved functional regulatory elements.</span></p><p>Address of the bookmark: <a href="https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm" rel="nofollow">https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35885/multi-car-a-tool-of-contig-scaffolding-using-multiple-references</guid>
	<pubDate>Tue, 06 Mar 2018 16:39:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35885/multi-car-a-tool-of-contig-scaffolding-using-multiple-references</link>
	<title><![CDATA[Multi-CAR: a tool of contig scaffolding using multiple references]]></title>
	<description><![CDATA[<p><span>we design a simple heuristic method to further revise our single reference-based scaffolding tool CAR into a new one called Multi-CAR such that it can utilize multiple complete genomes of related organisms as references to more accurately order and orient the contigs of a draft genome. In practical usage, our Multi-CAR does not require prior knowledge concerning phylogenetic relationships among the draft and reference genomes and libraries of paired-end reads. To validate Multi-CAR, we have tested it on a real dataset composed of several prokaryotic genomes and also compared its accuracy performance with other multiple reference-based scaffolding tools Ragout and MeDuSa.&nbsp;</span></p><p>Address of the bookmark: <a href="http://genome.cs.nthu.edu.tw/Multi-CAR/" rel="nofollow">http://genome.cs.nthu.edu.tw/Multi-CAR/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36755/minialign-fast-and-accurate-alignment-tool-for-pacbio-and-nanopore-long-reads</guid>
	<pubDate>Thu, 24 May 2018 08:33:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36755/minialign-fast-and-accurate-alignment-tool-for-pacbio-and-nanopore-long-reads</link>
	<title><![CDATA[minialign: fast and accurate alignment tool for PacBio and Nanopore long reads]]></title>
	<description><![CDATA[Minialign is a little bit fast and moderately accurate nucleotide sequence alignment tool designed for PacBio and Nanopore long reads. It is built on three key algorithms, minimizer-based index of the minimap overlapper, array-based seed chaining, and SIMD-parallel Smith-Waterman-Gotoh extension.<p>Address of the bookmark: <a href="https://github.com/ocxtal/minialign" rel="nofollow">https://github.com/ocxtal/minialign</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/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:39:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data</link>
	<title><![CDATA[SeqMonk:A tool to visualise and analyse high throughput mapped sequence data]]></title>
	<description><![CDATA[<p>SeqMonk is a program to enable the visualisation and analysis of mapped sequence data. It was written for use with mapped next generation sequence data but can in theory be used for any dataset which can be expressed as a series of genomic positions. It's main features are:</p>
<ul>
<li>Import of mapped data from mapped data (BAM/SAM/bowtie etc)</li>
<li>Creation of data groups for visualisation and analysis</li>
<li>Visualisation of mapped regions against an annotated genome.</li>
<li>Flexible quantitation of the mapped data to allow comparisons between data sets</li>
<li>Statistical analysis of data to find regions of interest</li>
<li>Creation of reports containing data and genome annotation</li>
</ul><p>Address of the bookmark: <a href="http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/" rel="nofollow">http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/</a></p>]]></description>
	<dc:creator>Jit</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/41669/filtlong-quality-filtering-tool-for-long-reads</guid>
	<pubDate>Wed, 13 May 2020 10:23:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41669/filtlong-quality-filtering-tool-for-long-reads</link>
	<title><![CDATA[Filtlong: quality filtering tool for long reads]]></title>
	<description><![CDATA[<p>Filtlong is a tool for filtering long reads by quality. It can take a set of long reads and produce a smaller, better subset. It uses both read length (longer is better) and read identity (higher is better) when choosing which reads pass the filter.</p>
<p>Filtlong builds into a stand-alone executable:</p>
<pre><code>git clone https://github.com/rrwick/Filtlong.git
cd Filtlong
make -j
bin/filtlong -h
</code></pre><p>Address of the bookmark: <a href="https://github.com/rrwick/Filtlong" rel="nofollow">https://github.com/rrwick/Filtlong</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs</guid>
	<pubDate>Tue, 30 Jun 2020 21:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs</link>
	<title><![CDATA[truvari: Structural variant comparison tool for VCFs]]></title>
	<description><![CDATA[<p>Structural variant comparison tool for VCFs</p>
<p>Given benchmark and comparsion sets of SVs, calculate the recall, precision, and f-measure.</p>
<p><a href="https://github.com/spiralgenetics/www.spiralgenetics.com">Spiral Genetics</a></p>
<p><a href="https://docs.google.com/presentation/d/17mvC1XOpOm7khAbZwF3SgtG2Rl4M9Mro37yF2nN7GhE/edit">Motivation</a></p><p>Address of the bookmark: <a href="https://github.com/spiralgenetics/truvari" rel="nofollow">https://github.com/spiralgenetics/truvari</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42354/vsfilt-a-tool-to-improve-virtual-screening-by-structural-filtration-of-docking-poses</guid>
	<pubDate>Wed, 25 Nov 2020 02:39:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42354/vsfilt-a-tool-to-improve-virtual-screening-by-structural-filtration-of-docking-poses</link>
	<title><![CDATA[vsFilt: A tool to improve virtual screening by structural filtration of docking poses]]></title>
	<description><![CDATA[<p><span>The vsFilt is the first open application for post-docking structural filtration, available as a web-server. The new tool is easy to use and configure to detect a wide range of interaction types that are known to be involved in molecular recognition, including hydrogen and halogen bonds, ionic interactions, hydrophobic contacts, &pi;-stacking, and cation-&pi; interactions. The web-server can process large libraries of up to 150&rsquo;000 docked ligand poses. The results are web-based and can be operated on-line using the built-in HTML5 interactive analysis tools, or can be downloaded for a local use. The vsFilt is freely available on-line, no login required.</span></p><p>Address of the bookmark: <a href="https://biokinet.belozersky.msu.ru/vsfilt" rel="nofollow">https://biokinet.belozersky.msu.ru/vsfilt</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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