<?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: All site bookmarks]]></title>
	<link>https://bioinformaticsonline.com/bookmarks/all?offset=340</link>
	<atom:link href="https://bioinformaticsonline.com/bookmarks/all?offset=340" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41582/flexidot-highly-customizable-ambiguity-aware-dotplots-for-visual-sequence-analyses</guid>
	<pubDate>Fri, 24 Apr 2020 08:39:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41582/flexidot-highly-customizable-ambiguity-aware-dotplots-for-visual-sequence-analyses</link>
	<title><![CDATA[flexidot: Highly customizable, ambiguity-aware dotplots for visual sequence analyses]]></title>
	<description><![CDATA[<p><span>FlexiDot is a cross-platform dotplot suite generating high quality self, pairwise and all-against-all visualizations. To improve dotplot suitability for comparison of consensus and error-prone sequences, FlexiDot harbors routines for strict and relaxed handling of mismatches and ambiguous residues. The custom shading modules facilitate dotplot interpretation and motif identification by adding information on sequence annotations and sequence similarities to the images. Combined with collage-like outputs, FlexiDot supports simultaneous visual screening of a large sequence sets, allowing dotplot use for routine screening.</span></p>
<p><img src="https://github.com/molbio-dresden/flexidot/blob/master/images/Beetle_matrix_shading.png?raw=true" alt="image" style="border: 0px; border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/molbio-dresden/flexidot" rel="nofollow">https://github.com/molbio-dresden/flexidot</a></p>]]></description>
	<dc:creator>Jit</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/41565/csar-web-a-web-server-of-contig-scaffolding-using-algebraic-rearrangements</guid>
	<pubDate>Fri, 10 Apr 2020 04:39:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41565/csar-web-a-web-server-of-contig-scaffolding-using-algebraic-rearrangements</link>
	<title><![CDATA[CSAR-web: a web server of contig scaffolding using algebraic rearrangements]]></title>
	<description><![CDATA[<p><span>CSAR-web is a web-based tool that allows the users to efficiently and accurately scaffold (i.e. order and orient) the contigs of a target draft genome based on a complete or incomplete reference genome from a related organism.&nbsp;</span></p>
<p><span><span>CSAR-web can serve as a convenient and useful scaffolding tool allowing the users to efficiently and accurately scaffold their draft genomes according to a complete or incomplete reference genome.&nbsp;</span></span></p><p>Address of the bookmark: <a href="http://genome.cs.nthu.edu.tw/CSAR-web" rel="nofollow">http://genome.cs.nthu.edu.tw/CSAR-web</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes</guid>
	<pubDate>Thu, 09 Apr 2020 04:56:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes</link>
	<title><![CDATA[Dahak: benchmarking and containerization of tools for analysis of complex non-clinical metagenomes.]]></title>
	<description><![CDATA[<p><span>Dahak is a software suite that integrates state-of-the-art open source tools for metagenomic analyses. Tools in the dahak software suite will perform various steps in metagenomic analysis workflows including data pre-processing, metagenome assembly, taxonomic and functional classification, genome binning, and gene assignment. We aim to deliver the analytical framework as a robust and reliable containerized workflow system, which will be free from dependency, installation, and execution problems typically associated with other open-source bioinformatics solutions. This will maximize the transparency, data provenance (i.e., the process of tracing the origins of data and its movement through the workflow), and reproducibility.</span></p>
<p><span>More at&nbsp;<a href="https://dahak-metagenomics.github.io/dahak/">https://dahak-metagenomics.github.io/dahak/</a></span></p><p>Address of the bookmark: <a href="https://github.com/dahak-metagenomics/dahak" rel="nofollow">https://github.com/dahak-metagenomics/dahak</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41504/quartataweb-user-friendly-server-developed-for-polypharmacological-and-chemogenomics-analyses</guid>
	<pubDate>Wed, 01 Apr 2020 10:30:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41504/quartataweb-user-friendly-server-developed-for-polypharmacological-and-chemogenomics-analyses</link>
	<title><![CDATA[QuartataWeb: user-friendly server developed for polypharmacological and chemogenomics analyses.]]></title>
	<description><![CDATA[<p><span>Data on protein-drug and protein-chemical interactions are rapidly accumulating in databases such as&nbsp;</span><a href="http://www.drugbank.ca/" target="_blank">DrugBank</a><span>&nbsp;and&nbsp;</span><a href="http://stitch.embl.de/" target="_blank">STITCH</a><span>. These data usually reflect observed interactions, while the lack of data for a given protein-drug/chemical pair does not necessarily mean the lack of interaction. Indeed, recent studies, both computational and experimental, highlighted the promiscuity of both proteins and small molecules: many drugs have side effects i.e. they target proteins other than those known in public databases; and many proteins bind chemicals other than those known, opening the way to design repurposable drugs, new chemicals, or polypharmacological treatments.</span></p>
<p><span><a href="https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa210/5813333">https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa210/5813333</a></span></p><p>Address of the bookmark: <a href="http://quartata.csb.pitt.edu/" rel="nofollow">http://quartata.csb.pitt.edu/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41501/hicanu-accurate-assembly-of-segmental-duplications-satellites-and-allelic-variants-from-high-fidelity-long-reads</guid>
	<pubDate>Fri, 27 Mar 2020 22:49:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41501/hicanu-accurate-assembly-of-segmental-duplications-satellites-and-allelic-variants-from-high-fidelity-long-reads</link>
	<title><![CDATA[HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads]]></title>
	<description><![CDATA[<p><span>HiCanu, a significant modification of the Canu assembler designed to leverage the full potential of HiFi reads via homopolymer compression, overlap-based error correction, and aggressive false overlap filtering.&nbsp;</span></p>
<p>More at&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.03.14.992248v3?fbclid=IwAR2PaN4GLjvAZpWmCE2q0EWk2dtwY7wiKxVlXn9PPG7OBSP06PP2gcCrv3A">https://www.biorxiv.org/content/10.1101/2020.03.14.992248v3</a></p><p>Address of the bookmark: <a href="https://github.com/marbl/canu" rel="nofollow">https://github.com/marbl/canu</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41493/coronavirus-resources</guid>
	<pubDate>Wed, 25 Mar 2020 17:11:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41493/coronavirus-resources</link>
	<title><![CDATA[Coronavirus Resources !]]></title>
	<description><![CDATA[<p><span>2019nCoVR features comprehensive integration of genomic and proteomic sequences as well as their metadata information from the GISAID, NCBI, NMDC and CNCB/NGDC. It also incorporates a wide range of relevant information including scientific literatures, news, and popular articles for science dissemination, and provides visualization functionalities for genome variation analysis results based on all collected 2019-nCoV strains.</span></p>
<p><span>Annotation</span></p>
<p><span><a href="https://bigd.big.ac.cn/ncov/variation/annotation">https://bigd.big.ac.cn/ncov/variation/annotation</a></span></p>
<p><span>Genome wharehouse&nbsp;</span></p>
<p><span><a href="https://bigd.big.ac.cn/gwh/browse/index">https://bigd.big.ac.cn/gwh/browse/index</a></span></p>
<p>Released Genome</p>
<p><a href="https://bigd.big.ac.cn/ncov/release_genome">https://bigd.big.ac.cn/ncov/release_genome</a></p>
<p>Download data&nbsp;</p>
<p><a href="ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/">ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/</a></p>
<p>Raw data</p>
<p><a href="https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae">https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae</a></p><p>Address of the bookmark: <a href="https://bigd.big.ac.cn/ncov/about" rel="nofollow">https://bigd.big.ac.cn/ncov/about</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41487/tinycov-standalone-command-line-utility-written-in-python-to-plot-coverage-from-a-bam-file</guid>
	<pubDate>Mon, 23 Mar 2020 06:22:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41487/tinycov-standalone-command-line-utility-written-in-python-to-plot-coverage-from-a-bam-file</link>
	<title><![CDATA[tinycov: standalone command line utility written in python to plot coverage from a BAM file]]></title>
	<description><![CDATA[<p>Tinycov is a small standalone command line utility written in python to plot the coverage of a BAM file quickly. This software was inspired by&nbsp;<a href="https://github.com/matted/genome_coverage_plotter">Matt Edwards' genome coverage plotter</a>.</p>
<p>To install the stable version:&nbsp;<code>pip3 install --user tinycov</code></p>
<p>To install the development version:</p>
<pre><code>git clone https://github.com/cmdoret/tinycov.git
cd tinycov
pip install .</code></pre><p>Address of the bookmark: <a href="https://github.com/cmdoret/tinycov" rel="nofollow">https://github.com/cmdoret/tinycov</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41485/chromosight-computer-vision-based-program-for-pattern-recognition-in-chromosome-hi-c-contact-maps</guid>
	<pubDate>Mon, 23 Mar 2020 06:20:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41485/chromosight-computer-vision-based-program-for-pattern-recognition-in-chromosome-hi-c-contact-maps</link>
	<title><![CDATA[chromosight: Computer vision based program for pattern recognition in chromosome (Hi-C) contact maps]]></title>
	<description><![CDATA[<p>Python package to detect chromatin loops (and other patterns) in Hi-C contact maps.</p>
<p>Stable version with pip:</p>
<div>
<pre>pip3 install --user chromosight</pre>
</div>
<p>Stable version with conda:</p>
<div>
<pre>conda install -c bioconda -c conda-forge chromosight</pre>
</div>
<p>or, if you want to get the latest development version:</p>
<pre><code>pip3 install --user -e git+https://github.com/koszullab/chromosight.git@master#egg=chromosight</code></pre><p>Address of the bookmark: <a href="https://github.com/koszullab/Chromosight" rel="nofollow">https://github.com/koszullab/Chromosight</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41482/magic-blast</guid>
	<pubDate>Fri, 20 Mar 2020 15:18:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41482/magic-blast</link>
	<title><![CDATA[Magic-BLAST]]></title>
	<description><![CDATA[<p>Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.</p><p>Address of the bookmark: <a href="https://ncbi.github.io/magicblast/" rel="nofollow">https://ncbi.github.io/magicblast/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>

</channel>
</rss>