<?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: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43639?offset=40</link>
	<atom:link href="https://bioinformaticsonline.com/related/43639?offset=40" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44483/baclife-an-automated-genome-mining-tool-for-identification-of-lifestyle-associated-genes</guid>
	<pubDate>Fri, 15 Mar 2024 04:59:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44483/baclife-an-automated-genome-mining-tool-for-identification-of-lifestyle-associated-genes</link>
	<title><![CDATA[bacLIFE: an automated genome mining tool for identification of lifestyle associated genes]]></title>
	<description><![CDATA[<p style="margin-top: 0px; margin-bottom: 16px; color: #1f2328; font-size: 16px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff;" dir="auto">bacLIFE is a streamlined computational workflow that annotates bacterial genomes and performs large-scale comparative genomics to predict bacterial lifestyles and to pinpoint candidate genes, denominated<span>&nbsp;</span><strong style="font-weight: var(--base-text-weight-semibold, 600);">lifestyle-associated genes (LAGs)</strong>, and biosynthetic gene clusters associated with each lifestyle detected. This whole process is divided into different modules:</p>
<ul style="margin-top: 0px; margin-bottom: 16px; color: #1f2328; font-size: 16px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff;" dir="auto">
<li><strong style="font-weight: var(--base-text-weight-semibold, 600);">Clustering module</strong><span>&nbsp;</span>Predicts, clusters and annotates the genes of every input genome</li>
<li style="margin-top: 0.25em;"><strong style="font-weight: var(--base-text-weight-semibold, 600);">Lifestyle prediction</strong><span>&nbsp;</span>Employs a machine learning model to forecast bacterial lifestyle or other specified metadata</li>
<li style="margin-top: 0.25em;"><strong style="font-weight: var(--base-text-weight-semibold, 600);">Analitical module (Shiny app)</strong><span>&nbsp;</span>Results from the previous modules are embedded in a user-friendly interface for comprehensive and interactive comparative genomics.</li>
</ul>
<p style="margin-top: 0px; margin-bottom: 16px; color: #1f2328; font-size: 16px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff;" dir="auto">You can find the complete wiki here [<a href="https://github.com/Carrion-lab/bacLIFE/wiki/bacLIFE-wiki">https://github.com/Carrion-lab/bacLIFE/wiki/bacLIFE-wiki</a>]</p><p>Address of the bookmark: <a href="https://github.com/Carrion-lab/bacLIFE" rel="nofollow">https://github.com/Carrion-lab/bacLIFE</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44898/genomad-identification-of-mobile-genetic-elements</guid>
	<pubDate>Sun, 31 Aug 2025 06:40:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44898/genomad-identification-of-mobile-genetic-elements</link>
	<title><![CDATA[geNomad: Identification of mobile genetic elements]]></title>
	<description><![CDATA[<p><span>geNomad is a tool that identifies virus and plasmid genomes from nucleotide sequences. It provides state-of-the-art classification performance and can be used to quickly find mobile genetic elements from genomes, metagenomes, or metatranscriptomes.</span></p><p>Address of the bookmark: <a href="https://portal.nersc.gov/genomad" rel="nofollow">https://portal.nersc.gov/genomad</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4408/fourth-branch-of-life</guid>
	<pubDate>Mon, 09 Sep 2013 21:48:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4408/fourth-branch-of-life</link>
	<title><![CDATA[Fourth Branch of Life]]></title>
	<description><![CDATA[<p>Scientist have found the biggest viruses known, pandoraviruses which opened up entirely /completely... new questions questions and raise objections to in science. It even suggesting a fourth domain of life.</p><p>The new visrus are about one micron&mdash;a thousandth of a millimeter&mdash;in length, the newfound genus Pandoravirus dwarfs other viruses, which range in size from about 50 nanometers up to 100 nanometers. A genus is a taxonomic ranking between species and family.</p><p>Find&nbsp; more at @ http://www.nature.com/scitable/blog/viruses101/newly_found_pandoraviruses_hint_at</p><p>http://news.nationalgeographic.co.uk/news/2013/07/130718-viruses-pandoraviruses-science-biology-evolution/</p><p>&nbsp;</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43940/langya-virus-update</guid>
	<pubDate>Fri, 12 Aug 2022 05:31:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43940/langya-virus-update</link>
	<title><![CDATA[Langya Virus Update !]]></title>
	<description><![CDATA[<p>https://www.ncbi.nlm.nih.gov/nuccore/OM101125,OM101126,OM101127,OM101128,OM101129,OM101130?</p><p>Zoonotic Henipavirus</p><p>https://pubmed.ncbi.nlm.nih.gov/35921459/</p><p>https://www.ncbi.nlm.nih.gov/nuccore/OM069646,,OM069567,OM069568,OM069569,OM069570,OM069571,OM069572,OM069573,OM069574,OM069575,OM069576,OM069577,OM069578,OM069579,OM069580,OM069581,OM069582,OM069583,OM069584,OM069585,OM069586,OM069587,OM069588,OM069589,OM069590,OM069591,OM069592,OM069593,OM069594,OM069595,OM069596,OM069597,OM069598,OM069599,OM069600,OM069601,OM069602,OM069603,OM069604,OM069605,OM069606,OM069607,OM069608,OM069609,OM069610,OM069611,OM069612,OM069613,OM069614,OM069615,OM069616,OM069617,OM069618,OM069619,OM069620,OM069621,OM069622,OM069623,OM069624,OM069625,OM069626,OM069627,OM069628,OM069629,OM069630,OM069631,OM069632,OM069633,OM069634,OM069635,OM069636,OM069637,OM069638,OM069639,OM069640,OM069641,OM069642,OM069643,OM069644,OM069645,OM069646</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</guid>
	<pubDate>Mon, 05 Aug 2024 23:01:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</link>
	<title><![CDATA[UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment]]></title>
	<description><![CDATA[<p>UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment</p>
<ul>
<li>
<p>Using state of the art tools, easily extended for other viruses</p>
</li>
<li>
<p>Tool and database updates for critical components via Conda</p>
</li>
<li>
<p>Built using modern design patterns with Conda and Snakemake</p>
</li>
<li>
<p>Extensible and easy to customize</p>
</li>
<li>
<p>Submission Ready Genomes</p>
</li>
<li>
<p>Customizable reporting with comprehensive visualization</p>
</li>
</ul>
<p>https://ikim-essen.github.io/uncovar/</p>
<p>Github&nbsp;https://github.com/IKIM-Essen/uncovar</p>
<p>&nbsp;</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://ikim-essen.github.io/uncovar/" rel="nofollow">https://ikim-essen.github.io/uncovar/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6130/rna-bioinformatics-and-high-throughput-analysis-jena</guid>
  <pubDate>Sat, 09 Nov 2013 20:03:56 -0600</pubDate>
  <link></link>
  <title><![CDATA[RNA Bioinformatics and High Throughput Analysis Jena]]></title>
  <description><![CDATA[
<p>Research Topics:</p>

<p>High Throughput Sequencing Analysis<br />Comparative Genomics<br />Identification and Annotation of Non-coding RNAs<br />Bioinformatic Analysis and System Biology of Viruses<br />Coevolution of Proteins and RNAs<br />Algorithmic Bioinformatics<br />Phylogenetic Analysis</p>

<p>http://www.rna.uni-jena.de/index.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43084/frequently-used-bioinformatics-tools-for-viral-genome-analysis</guid>
	<pubDate>Wed, 23 Jun 2021 07:40:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43084/frequently-used-bioinformatics-tools-for-viral-genome-analysis</link>
	<title><![CDATA[Frequently used bioinformatics tools for viral genome analysis !]]></title>
	<description><![CDATA[<p><strong>IVA: accurate de novo assembly of RNA virus genomes.</strong><br /> Hunt M, Gall A, Ong SH, Brener J, Ferns B, Goulder P, Nastouli E, Keane JA, Kellam P, Otto TD.<br /> Bioinformatics. 2015 Jul 15;31(14):2374-6. doi: <a href="http://bioinformatics.oxfordjournals.org/content/31/14/2374.long">10.1093/bioinformatics/btv120</a>. Epub 2015 Feb 28.</p><p><a href="http://www.nature.com/nmeth/journal/v9/n1/full/nmeth.1814.html"><strong>Adapter sequences</strong></a>:<br /> <strong>Optimal enzymes for amplifying sequencing libraries.</strong><br /> Quail, M. a et al. Nat. Methods 9, 10-1 (2012).</p><p><a href="http://genome.cshlp.org/content/early/2012/01/12/gr.131383.111"><strong>GAGE</strong></a>:<br /> <strong>GAGE: A critical evaluation of genome assemblies and assembly algorithms.</strong><br /> Salzberg, S. L. et al. Genome Res. 22, 557-67 (2012).</p><p><a href="http://www.biomedcentral.com/1471-2105/14/160"><strong>KMC</strong></a>:<br /> <strong>Disk-based k-mer counting on a PC.</strong><br /> Deorowicz, S., Debudaj-Grabysz, A. &amp; Grabowski, S. BMC Bioinformatics 14, 160 (2013).</p><p><a href="http://genomebiology.com/2014/15/3/R46"><strong>Kraken</strong></a>:<br /> <strong>Kraken: ultrafast metagenomic sequence classification using exact alignments.</strong><br /> Wood, D. E. &amp; Salzberg, S. L. Genome Biol. 15, R46 (2014).</p><p><a href="http://genomebiology.com/2004/5/2/r12"><strong>MUMmer</strong></a>:<br /> <strong>Versatile and open software for comparing large genomes.</strong><br /> Kurtz, S. et al. Genome Biol. 5, R12 (2004).</p><p><strong>R</strong>:<br /> <strong>R: A language and environment for statistical computing.</strong><br /> R Core Team (2013). R Foundation for Statistical Computing, Vienna, Austria. URL <a href="http://www.R-project.org/">http://www.R-project.org/</a>.</p><p><a href="http://nar.oxfordjournals.org/content/39/9/e57"><strong>RATT</strong></a>:<br /> <strong>RATT: Rapid Annotation Transfer Tool.</strong><br /> Otto, T. D., Dillon, G. P., Degrave, W. S. &amp; Berriman, M. Nucleic Acids Res. 39, e57 (2011).</p><p><a href="http://bioinformatics.oxfordjournals.org/content/25/16/2078.abstract"><strong>SAMtools</strong></a>:<br /> <strong>The Sequence Alignment/Map format and SAMtools.</strong><br /> Li, H. et al. Bioinformatics 25, 2078-9 (2009).</p><p><a href="http://bioinformatics.oxfordjournals.org/content/early/2014/04/12/bioinformatics.btu170"><strong>Trimmomatic</strong></a>:<br /> <strong>Trimmomatic: A flexible trimmer for Illumina Sequence Data.</strong><br /> Bolger, A. M., Lohse, M. &amp; Usadel, B. Bioinformatics 1-7 (2014).</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38593/excavator-detecting-copy-number-variants-from-whole-exome-sequencing-data</guid>
	<pubDate>Fri, 04 Jan 2019 10:10:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38593/excavator-detecting-copy-number-variants-from-whole-exome-sequencing-data</link>
	<title><![CDATA[EXCAVATOR: detecting copy number variants from whole-exome sequencing data]]></title>
	<description><![CDATA[<p><span>EXCAVATOR, for the detection of copy number variants (CNVs) from whole-exome sequencing data. EXCAVATOR combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number states. We validate EXCAVATOR on three datasets and compare the results with three other methods. These analyses show that EXCAVATOR outperforms the other methods and is therefore a valuable tool for the investigation of CNVs in largescale projects, as well as in clinical research and diagnostics. EXCAVATOR is freely available at&nbsp;</span><span><a href="http://sourceforge.net/projects/excavatortool/" target="_blank"><span>http://sourceforge.net/projects/excavatortool/</span></a></span><span>.</span><br><br><br><span>EXCAVATOR is a novel software package for the detection of copy number variants (CNVs) from whole-exome sequencing data.</span><br><span>EXCAVATOR has been published on Genome Biology (</span><a href="http://genomebiology.com/2013/14/10/R120/abstract" target="_blank">http://genomebiology.com/2013/14/10/R120/abstract<span></span></a><span>).</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/excavatortool/" rel="nofollow">https://sourceforge.net/projects/excavatortool/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27845/cnidaria-fast-reference-free-phylogenomic-clustering</guid>
	<pubDate>Thu, 16 Jun 2016 17:55:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27845/cnidaria-fast-reference-free-phylogenomic-clustering</link>
	<title><![CDATA[CNIDARIA: fast, reference-free phylogenomic clustering]]></title>
	<description><![CDATA[<p>Motivation: Identification of biological specimens is a major requirement for a range of applications. Reference-free methods analyse unprocessed sequencing data without relying on prior knowledge, but these do not scale to arbitrarily large genomes and arbitrarily large phylogenetic distances.</p>
<p>Results: We present Cnidaria, a practical tool for clustering genomic and transcriptomic data with no limitation on ge-nome size or phylogenetic distances. We successfully simultaneously clustered 169 genomic and transcriptomic datasets from 4 kingdoms, achieving 100% accuracy at supra-species level and 78% accuracy for species level.</p>
<p>Availability and Implementation: Cnidaria is written in C++ and Python and is available at http://www.ab.wur.nl/cnidaria.</p>
<p>Contact: Saulo Aflitos - sauloal@gmail.com</p>
<p>Supplementary information: Supplementary data are available at Bioinformatics online.</p><p>Address of the bookmark: <a href="https://github.com/sauloal/cnidaria/wiki" rel="nofollow">https://github.com/sauloal/cnidaria/wiki</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>

</channel>
</rss>