<?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/37233?offset=170</link>
	<atom:link href="https://bioinformaticsonline.com/related/37233?offset=170" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/34212/webinar-on-unique-molecular-identifier-umi-powered-ultra-sensitive-variant-calling-using-strand-ngs-case-study</guid>
	<pubDate>Tue, 07 Nov 2017 03:55:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/34212/webinar-on-unique-molecular-identifier-umi-powered-ultra-sensitive-variant-calling-using-strand-ngs-case-study</link>
	<title><![CDATA[Webinar on Unique Molecular Identifier (UMI)-powered Ultra-sensitive Variant Calling using Strand NGS - Case Study]]></title>
	<description><![CDATA[<h2><a href="http://www.strand-ngs.com/webinar_registration">Webinar on Unique Molecular Identifier-powered Ultra-sensitive Variant Calling using Strand NGS - Case Study</a></h2><p>by&nbsp;Dr. Pandurang Kolekar, Bioinformatics Engineer, Strand Life Sciences</p><h3><a href="http://www.strand-ngs.com/webinar_registration">Abstract</a>:</h3><p>Unique Molecular Identifiers (UMIs) are short random nucleotide sequences that are increasingly being used in high-throughput sequencing experiments. In this webinar, we will highlight the UMI-friendly features of Strand NGS v3.1 including support for handling well known and customised UMI libraries, QC metrics, consensus alignment, UMI-based family size filters for read list, genome browser enabled with UMI-specific features and filters, UMI-aware variant calling parameters, and exporting UMI-tagged aligned samples. These all features together empower users to harness the potential of UMI-tagged NGS data for deeper insights. A case study demonstrating application of these UMI-based features in Strand NGS for low frequency variant calling in cfDNA sample will be presented.</p><p>UMI-tagged NGS libraries allow, ultra-sensitive detection of low frequency variants from liquid biopsy samples using DNA-Seq and accurate quantification of transcript-level expression using RNA-Seq. The recent release of Strand NGS v3.1, is equipped with the necessary features to efficiently analyse UMI-tagged NGS data helping researchers and labs involved in rare variant calling like in cfDNA based cancer diagnostics, and accurate transcript quantification with RNA-Seq.</p><p><a href="http://www.strand-ngs.com/webinar_registration"><strong>Webinar Details:</strong></a></p><p><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 1:</strong></a> 13 Dec 2017, 2:30 PM IST<br /><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 2:</strong></a> 13 Dec 2017, 9:30 PM IST</p><p><br /><a href="http://www.strand-ngs.com/webinar_registration"><strong>Register here:</strong></a> http://www.strand-ngs.com/webinar_registration</p><h3>&nbsp;</h3>]]></description>
	<dc:creator>Strand</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43308/rna-seq-differential-expression-work-flow-using-deseq2</guid>
	<pubDate>Mon, 23 Aug 2021 10:57:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43308/rna-seq-differential-expression-work-flow-using-deseq2</link>
	<title><![CDATA[RNA-Seq differential expression work flow using DESeq2]]></title>
	<description><![CDATA[<p><span>One of the aim of RNAseq data analysis is the detection of differentially expressed genes. The package&nbsp;</span><a href="http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html">DESeq2</a><span>&nbsp;provides methods to test for differential expression analysis.</span></p><p>Address of the bookmark: <a href="http://www.sthda.com/english/wiki/rna-seq-differential-expression-work-flow-using-deseq2" rel="nofollow">http://www.sthda.com/english/wiki/rna-seq-differential-expression-work-flow-using-deseq2</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/32950/genespring-webinar-uncovering-mechanisms-of-hepatotoxicity-on-14-june-at-8am-pst</guid>
	<pubDate>Tue, 23 May 2017 06:48:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/32950/genespring-webinar-uncovering-mechanisms-of-hepatotoxicity-on-14-june-at-8am-pst</link>
	<title><![CDATA[GeneSpring webinar- Uncovering mechanisms of hepatotoxicity on 14 June at 8AM PST]]></title>
	<description><![CDATA[<p><a href="http://genespring-support.com/content/webinar-uncovering-mechanisms-hepatotoxicity-high-affinity-antisense-oligonucleotides-using-"><strong>Uncovering Mechanisms of Hepatotoxicity for High Affinity Antisense Oligonucleotides &ndash; 3&rsquo; end RNA-seq Profiling Using GeneSpring GX</strong></a></p><p>High affinity antisense oligonucleotides (ASOs) containing bicylic modifications (BNA) such as locked nucleic acid (LNA) or constrained ethyl (cEt) designed to induce target RNA cleavage have been shown to have enhanced potency along with a higher propensity to cause hepatotoxicity. In order to unravel the mechanism of this hepatotoxicity, we leveraged GeneSpring GX analysis software to analyze transcriptional profiles from the livers of mice treated with a panel of highly efficacious hepatotoxic or non-hepatotoxic LNA ASOs.</p><p><a href="http://genespring-support.com/content/webinar-uncovering-mechanisms-hepatotoxicity-high-affinity-antisense-oligonucleotides-using-"><strong>Speaker:</strong></a><br />Sebastien A. Burel, PhD<br />Director, Nonclinical Development, Ionis Pharmaceuticals, California</p><p><a href="http://genespring-support.com/content/webinar-uncovering-mechanisms-hepatotoxicity-high-affinity-antisense-oligonucleotides-using-"><strong>Details:</strong></a><br />14 June 2017, 8 AM PST</p><h3><a href="http://genespring-support.com/content/webinar-uncovering-mechanisms-hepatotoxicity-high-affinity-antisense-oligonucleotides-using-">Register for this Webinar</a></h3>]]></description>
	<dc:creator>Yeshodari</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4728/3-days-intensive-course-on-understanding-omics-data-in-basel-switzerland-19-21st-november</guid>
  <pubDate>Mon, 23 Sep 2013 10:46:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[3 days intensive course on Understanding 'omics data in Basel, Switzerland, 19-21st November]]></title>
  <description><![CDATA[
<p>Benefits for the participants</p>

<p>- Plan more efficient experiments<br />- Correctly interpret results<br />- Communicate results in publications more effectively</p>

<p>The course focus is on methodologies, not on particular software tools. After the course participants should be able to apply the methods in their respective environment. However, during the course, hands-on sessions will be performed using the Genedata Expressionist® software, which enables participants to quickly apply the discussed methods and visualize results. No previous knowledge on Expressionist® is required; access to the software is free of charge during the course.</p>

<p>More @ http://www.dixa-fp7.eu/dixa-training/dixa-training-agenda/genedata-academy#!</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24178/essentials-of-statistics-and-data-analysis-using-r</guid>
  <pubDate>Mon, 31 Aug 2015 01:32:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Essentials of Statistics and Data Analysis using R]]></title>
  <description><![CDATA[
<p>Clinical Development Services Agency (CDSA) is an extramural unit of Translational Health Science and Technology Institute (THSTI), Department of Biotechnology, Ministry of Science &amp; Technology, Government of India. CDSA has a national mandate of strengthening capacity and capability building in the area of Clinical development and Translational Research.</p>

<p>CDSA is pleased to announce a 4 days hands-on training program on “Essentials of Statistics and Data Analysis using R” at ICGEB, Aruna Asaf Ali Road, New Delhi on December 1 – 4, 2015. This will involve developing and enhancing skills to understand basic principles of statistics for summarizing data and use of appropriate statistical tests as well as providing an understanding of data analysis using R. Didactic lectures with practical sessions will be delivered by experienced faculties from AIIMS and Novartis. Live classroom with power point presentations, case studies, mock exercise, practical sessions on R, group work with time for discussion and Q&amp;A sessions are added advantages of this workshop.</p>

<p>Please contact gayatrivishwakarma.cdsa@thsti.res.in or vineetabaloni.cdsa@thsti.res.in for program and registration details.</p>

<p>Please nominate personage or register yourself on or before November 6, 2015 along with the electronic transfer of registration fee.</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/45140/integration-of-speciation-research-workshop-announcement</guid>
  <pubDate>Tue, 28 Apr 2026 07:07:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Integration Of Speciation Research : Workshop Announcement]]></title>
  <description><![CDATA[
<p>We are excited to share that the ESEB- funded special topic network Integration Of Speciation Research (IOS - https://speciation-network.pages.ist.ac.at/) is hosting a second in-person workshop from 7â€“11 December 2026 at the Scottish Centre for Ecology &amp; the Natural Environment (Glasgow, UK - https://www.gla.ac.uk/research/az/scene/).</p>

<p>This workshop is aimed at bringing together ~40 diverse speciation researchers:</p>

<p>-  to collaborate on populating a database of published reproductive barriers based on a standardized RIO framework (https://ecoevorxiv.org/repository/view/10083/). This will involve working through papers during the workshop to extract RI measures and other metadata and entering them into a draft database (some preparatory work before the workshop may be requested to facilitate these steps during the workshop)</p>

<p>- to start working towards a manuscript using this database to answer an outstanding question in speciation</p>

<p>- to network, learn about reproductive isolation, and have fun!</p>

<p>If you are interested in applying to participate in the workshop, please fill out the form in the link below by ** May 20th **. Room &amp; board will be covered by the organizers; all other travel costs are the responsibility of the attendee.</p>

<p>Application link:</p>

<p>https://docs.google.com/forms/d/e/1FAIpQLSenAMqSdZjeRmKEDtBNa5tpjPn7IukPyT5BzfZ4JMpIk2YOEw/viewform</p>

<p>The previous IOS workshop was held in Finland in 2023 (see more details at https://speciation-network.pages.ist.ac.at/workshops) and resulted in new interactions between speciation researchers and the successful publication of an Integration of Speciation research manuscript  (https://academic.oup.com/evolinnean/article/3/1/kzae001/7609448).</p>

<p>We look forward to seeing you in Glasgow!</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17176/arvados</guid>
	<pubDate>Sat, 20 Sep 2014 16:54:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17176/arvados</link>
	<title><![CDATA[Arvados]]></title>
	<description><![CDATA[<p>Arvados is a free and open&nbsp;source bioinformatics&nbsp;platform for genomic and&nbsp;biomedical data. User can&nbsp;Store | Organize | Compute | Share the data for free.&nbsp;</p>
<p><img src="https://arvados.org/images/dax.png" width="400" height="535" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://arvados.org/" rel="nofollow">https://arvados.org/</a></p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29654/randomness-and-probability</guid>
	<pubDate>Tue, 08 Nov 2016 07:17:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29654/randomness-and-probability</link>
	<title><![CDATA[Randomness and Probability]]></title>
	<description><![CDATA[<p>Randomness and Probability</p><p>Randomness and probability are two differnet concepts: probaility is a measure (according to measure theory) which measures the randomness. Randomness is the object to be measured by probability.&nbsp;For example, probability is a mapping from randomness to the real number between 0 and 1. The similar examples are that the entropy measures the uncertanity; product of length and width measures the area of rectangle etc.</p><p><strong>Please see &ldquo;A mathematical theory of ability measure&rdquo; by N. Kong ets for more examples to answer&nbsp;this question.</strong></p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29654" length="598559" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30459/prodigal-prokaryotic-dynamic-programming-genefinding-algorithm</guid>
	<pubDate>Thu, 29 Dec 2016 03:26:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30459/prodigal-prokaryotic-dynamic-programming-genefinding-algorithm</link>
	<title><![CDATA[Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm)]]></title>
	<description><![CDATA[<p><span>Prodigal (</span><strong>Pro</strong><span>karyotic&nbsp;</span><strong>Dy</strong><span>namic Programming&nbsp;</span><strong>G</strong><span>enefinding&nbsp;</span><strong>Al</strong><span>gorithm) is a microbial (bacterial and archaeal) gene finding program developed at Oak Ridge National Laboratory and the University of Tennessee. Key features of Prodigal include:</span></p>
<ul>
<li><strong>Speed</strong>: Prodigal is an extremely fast gene recognition tool (written in very vanilla C). It can analyze an entire microbial genome in 30 seconds or less.</li>
<li><strong>Accuracy</strong>: Prodigal is a highly accurate gene finder. It correctly locates the 3' end of every gene in the experimentally verified Ecogene data set (except those containing introns). It possesses a very sophisticated ribosomal binding site scoring system that enables it to locate the translation initiation site with great accuracy (96% of the 5' ends in the Ecogene data set are located correctly).</li>
<li><strong>Specificity</strong>: Prodigal's false positive rate compares favorably with other gene identification programs, and usually falls under 5%.</li>
<li><strong>GC-Content Indifferent</strong>: Prodigal performs well even in high GC genomes, with over a 90% perfect match (5'+3') to the&nbsp;<em>Pseudomonas aeruginosa</em>&nbsp;curated annotations.</li>
<li><strong>Metagenomic Version</strong>: Prodigal can run in metagenomic mode and analyze sequences even when the organism is unknown.</li>
<li><strong>Ease of Use</strong>: Prodigal can be run in one step on a single genomic sequence or on a draft genome containing many sequences. It does not need to be supplied with any knowledge of the organism, as it learns all the properties it needs to on its own.</li>
<li><strong>Open Source</strong>: Prodigal source code is freely available under the General Public License.</li>
</ul>
<p>&nbsp;</p>
<div style="text-align: center;"><strong>Download the latest version of Prodigal at&nbsp;<a href="http://github.com/hyattpd/prodigal/releases/">the Prodigal github page.</a></strong>&nbsp;<br>or&nbsp;<br><strong>Browse the&nbsp;<a href="http://github.com/hyattpd/prodigal/wiki">wiki documenation.</a></strong>&nbsp;</div><p>Address of the bookmark: <a href="http://prodigal.ornl.gov/" rel="nofollow">http://prodigal.ornl.gov/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30701/harvest</guid>
	<pubDate>Tue, 31 Jan 2017 10:57:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30701/harvest</link>
	<title><![CDATA[Harvest]]></title>
	<description><![CDATA[<p>Harvest is a suite of core-genome alignment and visualization tools for quickly analyzing thousands of intraspecific microbial genomes, including variant calls, recombination detection, and phylogenetic trees.</p>
<p><a href="http://harvest.readthedocs.io/en/latest/_images/screen.png"><img src="http://harvest.readthedocs.io/en/latest/_images/screen.png" alt="_images/screen.png" style="border: 0px;"></a><span></span></p>
<p><strong>Tools</strong></p>
<ul>
<li><a href="http://harvest.readthedocs.io/en/latest/content/parsnp.html">Parsnp</a>&nbsp;- Core-genome alignment and analysis</li>
<li><a href="http://harvest.readthedocs.io/en/latest/content/gingr.html">Gingr</a>&nbsp;- Interactive visualization of alignments, trees and variants</li>
<li><a href="http://harvest.readthedocs.io/en/latest/content/harvest-tools.html">HarvestTools</a>&nbsp;- Archiving and postprocessing</li>
</ul>
<p><strong>Citation</strong></p>
<blockquote>
<div>Treangen TJ, Ondov BD, Koren S, Phillippy AM. The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biology, 15 (11), 1-15 [<a href="http://www.biomedcentral.com/content/pdf/s13059-014-0524-x.pdf">PDF</a>]</div>
</blockquote><p>Address of the bookmark: <a href="http://harvest.readthedocs.io/en/latest/index.html" rel="nofollow">http://harvest.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>