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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44628?offset=250</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</guid>
	<pubDate>Wed, 21 Feb 2024 06:19:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</link>
	<title><![CDATA[pipesnake: bioinformatics best-practice analysis pipeline for phylogenomic reconstruction]]></title>
	<description><![CDATA[<p dir="auto"><span>ausarg/pipesnake</span>&nbsp;is a bioinformatics best-practice analysis pipeline for phylogenomic reconstruction starting from short-read 'second-generation' sequencing data.</p>
<p dir="auto">The pipeline is built using&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The&nbsp;<a href="https://www.nextflow.io/docs/latest/dsl2.html">Nextflow DSL2</a>&nbsp;implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.</p><p>Address of the bookmark: <a href="https://github.com/AusARG/pipesnake" rel="nofollow">https://github.com/AusARG/pipesnake</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</guid>
	<pubDate>Sun, 27 Jul 2014 20:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</link>
	<title><![CDATA[You and your friend have similar DNA !!!]]></title>
	<description><![CDATA[<p>New research out of Massachusetts claims that people often choose friends that are similar to them in genetics and they are more accurate than you might suppose. A study published on PNAS&nbsp;http://www.pnas.org/content/111/Supplement_3/10796.full found that people are apt to pick friends who are genetically similar to themselves - so much so that friends tend to be as alike at the genetic level as a person's fourth cousin.</p><div style="text-align: center;"><img src="http://i.kinja-img.com/gawker-media/image/upload/s--CwLwHa43--/18fbmlokxcmqcjpg.jpg" alt="image" width="300" height="271" style="border: 0px; border: 0px;"></div><p>Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes &mdash; a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population.&nbsp;</p><p>The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.</p><p>Reference:</p><p>http://www.pnas.org/content/111/Supplement_3/10796.full</p><p>Image : http://i.kinja-img.com</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42963/davi-deep-learning-based-tool-for-alignment-and-single-nucleotide-variant-identification</guid>
	<pubDate>Tue, 16 Mar 2021 05:41:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42963/davi-deep-learning-based-tool-for-alignment-and-single-nucleotide-variant-identification</link>
	<title><![CDATA[DAVI: Deep learning-based tool for alignment and single nucleotide variant identification]]></title>
	<description><![CDATA[<p>DAVI consists of models for both global and local alignment and for variant calling. We have evaluated the performance of DAVI against existing state-of-the-art tool sets and found that its accuracy and performance is comparable to existing tools used for bench-marking. We further demonstrate that while existing tools are based on data generated from a specific sequencing technology, the models proposed in DAVI are generic and can be used across different NGS technologies as well as across different species</p>
<p>https://iopscience.iop.org/article/10.1088/2632-2153/ab7e19/pdf</p><p>Address of the bookmark: <a href="https://github.com/gguptaiitd/NEAT" rel="nofollow">https://github.com/gguptaiitd/NEAT</a></p>]]></description>
	<dc:creator>Jit</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/news/view/42470/the-new-corona-variant-has-23-mutations-in-all-which-is-unusually-huge</guid>
	<pubDate>Wed, 23 Dec 2020 03:50:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42470/the-new-corona-variant-has-23-mutations-in-all-which-is-unusually-huge</link>
	<title><![CDATA[The new corona variant has 23 mutations in all, which is unusually huge !]]></title>
	<description><![CDATA[<p>The new SARS-CoV-2 version, B.1.1.7, which was first seen in the third week of September in Kent and Greater London, has since spread to other locations in the UK. According to the COVID-19 Genomics UK Consortium (COG-UK Consortium) that analysed the genome data of the virus and identified the variant, the new variant has been spreading "rapidly" over the last four weeks and has now been detected in other locations in the UK, suggesting further spread of the variant in the region.</p><p><span>According to a<span>&nbsp;</span></span><a href="https://virological.org/t/preliminary-genomic-characterisation-of-an-emergent-sars-cov-2-lineage-in-the-uk-defined-by-a-novel-set-of-spike-mutations/563"><strong><span>preliminary report</span></strong></a><span><span>&nbsp;</span>posted on December 19 by the COG-UK Consortium scientists, as of December 15, 1,623 variant genomes have been sequenced. In a<span>&nbsp;</span></span><a href="https://twitter.com/TheCGPS/status/1340749351803629569"><strong><span>December 21 tweet</span></strong></a><span>, COG-UK Consortium said that it added 2,963 more genome sequences of SARS-CoV-2, of which 942 (32%) belong to the new variant. The Consortium<span>&nbsp;</span></span><a href="https://twitter.com/CovidGenomicsUK/status/1341073233420955654"><strong><span>intends to sequence</span></strong></a><span><span>&nbsp;</span>20,000 more SARS-CoV-2 genomes in the next two weeks to further ascertain the spread of the variant.</span></p><p><span>There is no clear proof, at least not yet, that it does cause severe pandemic. But there is a justification for seriously taking the possibility. Another coronavirus lineage in South Africa has acquired one specific mutation that is also present in B.1.1.7. This variant is increasingly spreading across South Africa's coastal regions. And doctors have observed in preliminary research that individuals infected with this variant bear a higher viral load-a higher concentration of the virus in their upper respiratory tract. In many viral diseases, this is associated with more severe symptoms.</span></p><p>&nbsp;</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2756/flu-attack-how-a-virus-invades-your-body</guid>
	<pubDate>Thu, 22 Aug 2013 08:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2756/flu-attack-how-a-virus-invades-your-body</link>
	<title><![CDATA[Flu Attack! How A Virus Invades Your Body]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/Rpj0emEGShQ" frameborder="0" allowfullscreen></iframe>When you get the flu, viruses turn your cells into tiny factories that help spread the disease. In this animation, NPR's Robert Krulwich and medical animator David Bolinsky explain how a flu virus can trick a single cell into making a million more viruses.

See and hear the rest of the story on NPR.org: http://www.npr.org/templates/story/story.php?storyId=114075029

Credit: Robert Krulwich, David Bolinsky, Jason Orfanon]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/38226/ncbi-to-assist-in-virus-hunting-data-science-hackathon</guid>
	<pubDate>Thu, 15 Nov 2018 12:55:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/38226/ncbi-to-assist-in-virus-hunting-data-science-hackathon</link>
	<title><![CDATA[NCBI to assist in Virus Hunting Data Science Hackathon]]></title>
	<description><![CDATA[<p>NCBI Hackathon are pleased to announce the second installment of the&nbsp;<a href="https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/30/ncbi-southern-california-genomics-hackathon-january/" target="_blank">SoCal Bioinformatics Hackathon</a>. From January 9-11, 2019, the&nbsp;<a href="https://www.ncbi.nlm.nih.gov/" target="_blank">NCBI</a>&nbsp;will help run a bioinformatics hackathon in Southern California hosted by the&nbsp;<a href="http://www.csrc.sdsu.edu/" target="_blank">Computational Sciences Research Center</a>&nbsp;at&nbsp;<a href="http://www.sdsu.edu/" target="_blank">San Diego State University</a>!</p><p><span>NCBI Hackathon</span>&nbsp;specifically looking for folks who have experience in computational virus hunting or adjacent fields to identify known, taxonomically-definable and novel viruses from a few hundred thousand metagenomic datasets that we&rsquo;ll put on cloud infrastructure. This event is for researchers, including students and postdocs, who are already engaged in the use of bioinformatics data or in the development of pipelines for virological analyses from high-throughput experiments. If this describes you, please&nbsp;<a href="https://goo.gl/forms/kDnSG0IAZD62XQRe2" target="_blank">apply</a>! The event is open to anyone selected for the hackathon and willing to travel to SDSU (see below).</p><p>https://ncbiinsights.ncbi.nlm.nih.gov/2018/11/09/ncbi-sdsu-virus-hunting-data-science-hackathon-january-2019/</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44173/mpxv-bookmarks</guid>
	<pubDate>Mon, 19 Dec 2022 01:58:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44173/mpxv-bookmarks</link>
	<title><![CDATA[MPXV Bookmarks]]></title>
	<description><![CDATA[<p>MPVX infection across the globe</p>
<p><a href="https://www.google.com/url?q=https://www.cdc.gov/poxvirus/monkeypox/response/2022/world-map.html&amp;sa=D&amp;source=docs&amp;ust=1671439883060005&amp;usg=AOvVaw39WwSqp2A5TD8KjRvaaxzW" target="_blank">https://www.cdc.gov/poxvirus/monkeypox/response/2022/world-map.html</a></p><p>Address of the bookmark: <a href="https://www.cdc.gov/poxvirus/monkeypox/response/2022/world-map.html" rel="nofollow">https://www.cdc.gov/poxvirus/monkeypox/response/2022/world-map.html</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5731/influenza-animation-flu-virus-mechanism</guid>
	<pubDate>Thu, 17 Oct 2013 19:43:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5731/influenza-animation-flu-virus-mechanism</link>
	<title><![CDATA[Influenza animation - flu virus mechanism]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/YSgkoldBNkI" frameborder="0" allowfullscreen></iframe>Animation of the mechanism of an influenza virus and how Crucell's antibodies target the HA1 proteins on the virus and prevent further spread of influenza. 

Client: Crucell
Direction, Design & Animation: Daniel Lim, 2Preform
Music & Sound Design: Javier Barrero, Logical Disorder
Production Company: David Hager, All Terrain Media]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43639/fastv-detect-virus</guid>
	<pubDate>Sat, 11 Dec 2021 08:04:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43639/fastv-detect-virus</link>
	<title><![CDATA[fastv - detect virus]]></title>
	<description><![CDATA[<p><span>fastv is an ultra-fast tool for identification of SARS-CoV-2 and other microbes from sequencing data. It detects microbial sequences from FASTQ data, generates JSON reports and visualizes the result in HTML reports. This tool can be used to detect viral infectious diseases, like COVID-19. This tool supports both short reads (Illumina, BGI, etc.) and long reads (ONT, PacBio, etc.)</span></p><p>Address of the bookmark: <a href="https://github.com/OpenGene/fastv" rel="nofollow">https://github.com/OpenGene/fastv</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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