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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26306?offset=920</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</guid>
	<pubDate>Sat, 21 May 2016 22:42:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</link>
	<title><![CDATA[Bpipe - a tool for running and managing bioinformatics pipelines]]></title>
	<description><![CDATA[<p>Bpipe provides a platform for running big bioinformatics jobs that consist of a series of processing stages - known as 'pipelines'.</p>
<ul>
<li>January 20th, 2016 - New! Bpipe 0.9.9 released!</li>
<li>Download <a href="http://download.bpipe.org/versions/bpipe-0.9.9.tar.gz">latest</a>, <a href="http://download.bpipe.org">all</a></li>
<li><a href="http://docs.bpipe.org">Documentation</a></li>
<li><a href="https://groups.google.com/forum/#%21forum/bpipe-discuss">Mailing List</a> (Google Group)</li>
</ul>
<p>Bpipe has been published in <a href="http://bioinformatics.oxfordjournals.org/content/early/2012/04/11/bioinformatics.bts167.abstract">Bioinformatics</a>! If you use Bpipe, please cite:</p>
<p><em>Sadedin S, Pope B &amp; Oshlack A, Bpipe: A Tool for Running and Managing Bioinformatics Pipelines, Bioinformatics</em></p><p>Address of the bookmark: <a href="http://docs.bpipe.org/" rel="nofollow">http://docs.bpipe.org/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26375/ncbi-remap</guid>
	<pubDate>Thu, 11 Feb 2016 11:02:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26375/ncbi-remap</link>
	<title><![CDATA[NCBI Remap]]></title>
	<description><![CDATA[<p><span><span><strong>NCBI Remap</strong>. This tool is conceptually similar to liftOver in that in manages conversions between a pair of genome assemblies but it uses different methods to achieve these mappings. It is also available through a simple <a href="http://www.ncbi.nlm.nih.gov/genome/tools/remap">web interface</a> or you can use the <a href="http://www.ncbi.nlm.nih.gov/genome/tools/remap/docs/api">API for NCBI Remap</a>.</span></span></p>
<p><span><span>More at http://www.ncbi.nlm.nih.gov/genome/tools/remap</span></span></p>
<p><span><span>API http://www.ncbi.nlm.nih.gov/genome/tools/remap/docs/api</span></span></p><p>Address of the bookmark: <a href="http://www.ncbi.nlm.nih.gov/genome/tools/remap" rel="nofollow">http://www.ncbi.nlm.nih.gov/genome/tools/remap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28168/sam-flags</guid>
	<pubDate>Wed, 29 Jun 2016 15:38:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28168/sam-flags</link>
	<title><![CDATA[SAM flags]]></title>
	<description><![CDATA[<p>Decoding SAM flags</p>
<p>This utility makes it easy to identify what are the properties of a read based on its SAM flag value, or conversely, to find what the SAM Flag value would be for a given combination of properties.</p>
<p>To decode a given SAM flag value, just enter the number in the field below. The encoded properties will be listed under Summary below, to the right.</p><p>Address of the bookmark: <a href="https://broadinstitute.github.io/picard/explain-flags.html" rel="nofollow">https://broadinstitute.github.io/picard/explain-flags.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28121/kaiju</guid>
	<pubDate>Mon, 27 Jun 2016 11:23:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28121/kaiju</link>
	<title><![CDATA[Kaiju]]></title>
	<description><![CDATA[<p>Kaiju is a program for the taxonomic classification of metagenomic high-throughput sequencing reads. Each read is directly assigned to a taxon within the NCBI taxonomy by comparing it to a reference database containing microbial and viral protein sequences.</p>
<p>By default, Kaiju uses either the available complete genomes from NCBI RefSeq or the microbial subset of the non-redundant protein database <em>nr</em> used by NCBI BLAST, optionally also including fungi and microbial eukaryotes.</p>
<p>Kaiju translates reads into amino acid sequences, which are then searched in the database using a modified backward search on a memory-efficient implementation of the Burrows-Wheeler transform, which finds maximum exact matches (MEMs), optionally allowing mismatches in the protein alignment. The search can process up to millions of reads per minute using, for example, only 10 GB RAM with a protein database comprising 4821 microbial genomes. Kaiju can also be used for querying any other protein database without taxonomic classification, using either protein or nucleotide queries.</p>
<p>Kaiju is described in <a href="http://www.nature.com/ncomms/2016/160413/ncomms11257/full/ncomms11257.html">Menzel, P. et al. (2016) Fast and sensitive taxonomic classification for metagenomics with Kaiju. <em>Nat. Commun.</em> 7:11257</a> (open access).</p><p>Address of the bookmark: <a href="http://kaiju.binf.ku.dk/" rel="nofollow">http://kaiju.binf.ku.dk/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</guid>
	<pubDate>Thu, 20 Dec 2018 17:39:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</link>
	<title><![CDATA[Genome Annotation using MAKER tutorial !]]></title>
	<description><![CDATA[<p><a href="http://www.yandell-lab.org/software/maker.html">MAKER</a><span>&nbsp;is a great tool for annotating a reference genome using empirical and&nbsp;</span><em>ab initio</em><span>gene predictions.&nbsp;</span><a href="http://gmod.org/wiki/Main_Page">GMOD</a><span>, the umbrella organization that includes MAKER, has some nice tutorials online for running MAKER. However, these were quite simplified examples and it took a bit of effort to wrap my head completely around everything. Here I will describe a&nbsp;</span><em>de novo</em><span>&nbsp;genome annotation for&nbsp;</span><em>Boa constrictor</em><span>&nbsp;in detail, so that there is a record and that it is easy to use this as a guide to annotate any genome.</span></p><p>Address of the bookmark: <a href="https://www.biostars.org/p/261203/" rel="nofollow">https://www.biostars.org/p/261203/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28415/scarpa</guid>
	<pubDate>Wed, 13 Jul 2016 07:59:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28415/scarpa</link>
	<title><![CDATA[Scarpa]]></title>
	<description><![CDATA[<p><strong>Scarpa</strong>&nbsp;is a stand-alone scaffolding tool for NGS data. It can be used together with virtually any genome assembler and any NGS read mapper that supports SAM format. Other features include support for multiple libraries and an option to estimate insert size distributions from data. Scarpa is available free of charge for academic and commercial use under the GNU General Public License (GPL).</p>
<p>See the&nbsp;<a href="http://compbio.cs.toronto.edu/hapsembler/hapsembler-2.21_manual.pdf">user manual</a>&nbsp;or the&nbsp;<a href="http://compbio.cs.toronto.edu/hapsembler/scarpa_paper.pdf">paper</a>&nbsp;for more information about Scarpa. Click&nbsp;<a href="http://compbio.cs.toronto.edu/hapsembler/ScarpaSupplementary.pdf">here</a>&nbsp;for the supplementary material.</p><p>Address of the bookmark: <a href="http://compbio.cs.toronto.edu/hapsembler/scarpa.html" rel="nofollow">http://compbio.cs.toronto.edu/hapsembler/scarpa.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</guid>
	<pubDate>Sun, 12 Apr 2020 10:02:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</link>
	<title><![CDATA[WEGO : simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results]]></title>
	<description><![CDATA[<p><span>WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary became more and more popular, WEGO was widely adopted and used in many researches. Therefore we have updated WEGO 2.0 in 2018. Here are some changes we&rsquo;ve made:</span><br><span>1. The limit of input file numbers was cancelled. Now the users could upload as many files as they want with one operation.</span><br><span>2. We have added the reference data of 9 species for users selection.</span><br><span>3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.</span></p><p>Address of the bookmark: <a href="http://wego.genomics.org.cn/" rel="nofollow">http://wego.genomics.org.cn/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38579/genomeview-genome-browser-and-annotation-editor</guid>
	<pubDate>Wed, 02 Jan 2019 04:09:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38579/genomeview-genome-browser-and-annotation-editor</link>
	<title><![CDATA[GenomeView: genome browser and annotation editor]]></title>
	<description><![CDATA[<p><span>GenomeView is a genome browser and annotation editor that displays reference sequence, annotation, multiple alignments, short read alignments and graphs. Most major data formats are supported. Local and internet files can be loaded.</span><br><span>This project has moved to GitHub:&nbsp;</span><a href="https://github.com/GenomeView/genomeview" target="_blank">https://github.com/GenomeView/genomeview</a></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/genomeview/" rel="nofollow">https://sourceforge.net/projects/genomeview/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43062/jcvi-utility-libraries</guid>
	<pubDate>Sat, 08 May 2021 22:04:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43062/jcvi-utility-libraries</link>
	<title><![CDATA[JCVI utility libraries]]></title>
	<description><![CDATA[<p><span>Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.</span></p><p>Address of the bookmark: <a href="https://github.com/tanghaibao/jcvi" rel="nofollow">https://github.com/tanghaibao/jcvi</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</guid>
	<pubDate>Sat, 20 Sep 2025 09:34:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</link>
	<title><![CDATA[HiTE: a fast and accurate dynamic boundary adjustment approach for full-length Transposable Elements detection and annotation in Genome Assemblies]]></title>
	<description><![CDATA[<p dir="auto"><code>HiTE</code>&nbsp;is a Python software that uses a dynamic boundary adjustment approach to detect and annotate full-length Transposable Elements in Genome Assemblies. In comparison to other tools, HiTE demonstrates superior performance in detecting a greater number of full-length TEs.</p>
<div dir="auto">
<h2 dir="auto">panHiTE</h2>
<a href="https://github.com/CSU-KangHu/HiTE#panhite"></a></div>
<p dir="auto">We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.</p>
<p dir="auto">For detailed instructions, please refer to the&nbsp;<a href="https://github.com/CSU-KangHu/HiTE/wiki/panHiTE-tutorial">panHiTE tutorial</a>.</p><p>Address of the bookmark: <a href="https://github.com/CSU-KangHu/HiTE" rel="nofollow">https://github.com/CSU-KangHu/HiTE</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

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