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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43645?</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43374/reference-sequence-resource</guid>
	<pubDate>Wed, 15 Sep 2021 21:15:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43374/reference-sequence-resource</link>
	<title><![CDATA[Reference Sequence Resource!]]></title>
	<description><![CDATA[<p><span>The ENCODE project uses Reference Genomes from&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/genome/browse/reference/">NCBI</a><span>&nbsp;or&nbsp;</span><a href="http://hgdownload.cse.ucsc.edu/downloads.html">UCSC</a><span>&nbsp;to provide a consistent framework for mapping high-throughput sequencing data.&nbsp;In general, ENCODE data are mapped consistently to 2 human (GRCH38, hg19) and 2 mouse (mm9/mm10) genomes for historical comparability.&nbsp;</span><em>Drosophia melanogaster</em><span>&nbsp;experiments are mapped to either dm3 or dm6 and&nbsp;</span><em>Caenorhabdilis elegans&nbsp;</em><span>experiments are mapped to ce10 or ce11.&nbsp;T</span></p><p>Address of the bookmark: <a href="https://www.encodeproject.org/data-standards/reference-sequences/" rel="nofollow">https://www.encodeproject.org/data-standards/reference-sequences/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44545/amr-database</guid>
	<pubDate>Tue, 04 Jun 2024 13:37:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44545/amr-database</link>
	<title><![CDATA[AMR Database !]]></title>
	<description><![CDATA[<ul>
<li><a href="http://en.mediterranee-infection.com/article.php?laref=283%26titre=arg-annot">ARG-ANNOT</a>. PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/24145532">24145532</a></li>
<li><a href="https://card.mcmaster.ca/">CARD</a>. PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/23650175">23650175</a></li>
<li><a href="https://megares.meglab.org/">MEGARes</a>&nbsp;PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/27899569">27899569</a></li>
<li><a href="https://www.ncbi.nlm.nih.gov/pathogens/isolates#/refgene/">NCBI</a>&nbsp;BioProject:&nbsp;<a href="https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA313047">PRJNA313047</a></li>
<li><a href="https://cge.cbs.dtu.dk/services/PlasmidFinder/">plasmidfinder</a>&nbsp;PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/24777092">24777092</a></li>
<li><a href="https://cge.cbs.dtu.dk//services/ResFinder/">resfinder</a>. PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/22782487">22782487</a></li>
<li><a href="http://www.mgc.ac.cn/VFs/">VFDB</a>. PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/26578559">26578559</a></li>
<li><a href="https://github.com/katholt/srst2">SRST2</a>'s version of ARG-ANNOT. PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/25422674">25422674</a>.</li>
<li><a href="https://cge.cbs.dtu.dk/services/VirulenceFinder/">VirulenceFinder</a>&nbsp;PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/24574290">24574290</a>.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/sanger-pathogens/ariba/wiki/Task%3A-getref" rel="nofollow">https://github.com/sanger-pathogens/ariba/wiki/Task%3A-getref</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43643/corona-virus-literature</guid>
	<pubDate>Sun, 12 Dec 2021 23:30:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43643/corona-virus-literature</link>
	<title><![CDATA[Corona Virus Literature !]]></title>
	<description><![CDATA[<p><span><span>LitCovid</span>&nbsp;is a curated literature hub for tracking up-to-date scientific information about the 2019 novel Coronavirus.</span><span>&nbsp;It is the most comprehensive resource on the subject, providing a central access to&nbsp;</span><span>201482</span><span>&nbsp;(and&nbsp;</span><span>growing</span><span>) relevant articles in PubMed. The articles are updated daily and are further categorized by different research topics (e.g.&nbsp;</span><span>Long Covid</span><span>) and geographic locations for improved access. You can learn more at&nbsp;</span><a href="https://www.nature.com/articles/d41586-020-00694-1" target="_blank">Chen et al. Nature</a><span>&nbsp;(2020) or our&nbsp;</span><span>FAQ</span><span>, and download our data&nbsp;</span><a href="https://www.ncbi.nlm.nih.gov/research/coronavirus/#data-download">here</a><span>.</span></p>
<p>https://www.ncbi.nlm.nih.gov/research/coronavirus/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/research/coronavirus/" rel="nofollow">https://www.ncbi.nlm.nih.gov/research/coronavirus/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43641/refseq-viraal-genome-sequences</guid>
	<pubDate>Sat, 11 Dec 2021 08:35:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43641/refseq-viraal-genome-sequences</link>
	<title><![CDATA[Refseq viraal genome sequences !]]></title>
	<description><![CDATA[<p>List of all viruses on NCBI&nbsp;</p>
<p>https://ftp.ncbi.nlm.nih.gov/refseq/release/viral/</p><p>Address of the bookmark: <a href="https://ftp.ncbi.nlm.nih.gov/refseq/release/viral/" rel="nofollow">https://ftp.ncbi.nlm.nih.gov/refseq/release/viral/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41886/coronavirus-sars-cov-2</guid>
	<pubDate>Wed, 17 Jun 2020 11:18:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41886/coronavirus-sars-cov-2</link>
	<title><![CDATA[Coronavirus SARS-CoV-2]]></title>
	<description><![CDATA[<p><span>Used Nanographics Vj, our real-time molecular visualization and animation software, to create this video showing the structure of the virus. In the video, you can see the latest theory on how the RNA is organized inside of the virus particle.</span></p>
<p><span><span>On this page, you can download&nbsp;</span><a href="https://nanographics.at/projects/sars-cov-2/sars-cov-2-renders.zip">high resolution images</a><span>&nbsp;of our renderings. We made them with transparent background, so that you can use it in your work. As the research progresses, we will keep updating the model as well as the images on this page, so stay tuned!</span></span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://nanographics.at/projects/sars-cov-2/" rel="nofollow">https://nanographics.at/projects/sars-cov-2/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</guid>
	<pubDate>Fri, 02 Feb 2018 03:24:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</link>
	<title><![CDATA[karyoploteR: plot whole genomes with arbitrary data]]></title>
	<description><![CDATA[<p><span><a href="http://bioconductor.org/packages/karyoploteR">karyoploteR</a></span><span>&nbsp;is an R package to create karyoplots, that is, representations of whole genomes with arbitrary data plotted on them. It is inspired by the R base graphics system and does not depend on other graphics packages. The aim of karyoploteR is to offer the user an easy way to plot data along the genome to get broad genome-wide view to facilitate the identification of genome wide relations and distributions.</span></p><p>Address of the bookmark: <a href="https://bernatgel.github.io/karyoploter_tutorial/" rel="nofollow">https://bernatgel.github.io/karyoploter_tutorial/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</guid>
	<pubDate>Wed, 29 Nov 2017 16:44:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</link>
	<title><![CDATA[Scripts for the analysis of HGT in genome sequence data.]]></title>
	<description><![CDATA[<p><span>Scripts for the analysis of HGT in genome sequence data</span></p><p>Address of the bookmark: <a href="https://github.com/reubwn/hgt" rel="nofollow">https://github.com/reubwn/hgt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</guid>
	<pubDate>Thu, 19 Apr 2018 08:06:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</link>
	<title><![CDATA[Heap: a highly sensitive and accurate SNP detection tool for low-coverage high-throughput sequencing data]]></title>
	<description><![CDATA[<p><span>Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls SNPs at each site except for sites at the both end of reads or containing a minor allele supported by only one read. Performance comparison with existing tools showed that Heap achieved the highest F-scores with low coverage (7X) restriction-site associated DNA sequencing reads of sorghum and rice individuals. This will facilitate cost-effective GWAS and GP studies in this NGS era. Code and documentation of Heap are freely available from&nbsp;</span><a href="https://github.com/meiji-bioinf/heap">https://github.com/meiji-bioinf/heap</a><span>&nbsp;and our web site (</span><a href="http://bioinf.mind.meiji.ac.jp/lab/en/tools.html">http://bioinf.mind.meiji.ac.jp/lab/en/tools.html</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/meiji-bioinf/heap" rel="nofollow">https://github.com/meiji-bioinf/heap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</guid>
	<pubDate>Mon, 09 Jul 2018 05:27:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</link>
	<title><![CDATA[Epiviz: an interactive visualization tool for functional genomics data.]]></title>
	<description><![CDATA[<p><span>Epiviz is an interactive visualization tool for functional genomics data. It supports genome navigation like other genome browsers, but allows multiple visualizations of data within genomic regions using scatterplots, heatmaps and other user-supplied visualizations. It also includes data from the&nbsp;</span><a href="http://barcode.luhs.org/" target="_blank">Gene Expression Barcode project</a><span>&nbsp;for transcriptome visualization. It has a flexible plugin framework so users can add</span><a href="http://d3js.org/" target="_blank">d3</a><span>&nbsp;visualizations. You can see a video tour&nbsp;</span><a href="http://youtu.be/099c4wUxozA" target="_blank">here</a><span>.</span></p>
<p><span>https://bioconductor.org/packages/release/bioc/html/epivizr.html</span></p>
<p><span>https://github.com/epiviz</span></p>
<p><span>https://github.com/epiviz/epiviz</span></p><p>Address of the bookmark: <a href="https://epiviz.github.io/" rel="nofollow">https://epiviz.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</guid>
	<pubDate>Thu, 04 Oct 2018 16:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</link>
	<title><![CDATA[VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules]]></title>
	<description><![CDATA[<p>VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.</p>
<h5>&nbsp;</h5><p>Address of the bookmark: <a href="https://github.com/broadinstitute/VariantBam" rel="nofollow">https://github.com/broadinstitute/VariantBam</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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