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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/23584?offset=10</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12111/internship-program-with-arraygen-technolgies</guid>
  <pubDate>Sun, 22 Jun 2014 23:18:31 -0500</pubDate>
  <link></link>
  <title><![CDATA[Internship program with ArrayGen Technolgies]]></title>
  <description><![CDATA[
<p>Internship Program for Bioinformatics / Biotechnology Professionals Currently we offer positions to outstanding students interested in Next Generation Sequencing (NGS) data analysis. Applications are accepted throughout the year. Accepted students will be listed on web with their schedules. Accepted students can attend our future workshops and trainings freely at the specified venue.</p>

<p>Interested candidates may email their resume along with a cover letter to careers@arraygen.com</p>

<p>Official website: http://www.arraygen.com/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/23590/will-minion-nanopore-sequencing-increase-the-number-of-next-generation-sequencing-projects</guid>
	<pubDate>Tue, 04 Aug 2015 05:14:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/23590/will-minion-nanopore-sequencing-increase-the-number-of-next-generation-sequencing-projects</link>
	<title><![CDATA[Will MinION Nanopore sequencing increase the number of Next Generation Sequencing projects?]]></title>
	<description><![CDATA[<p>Will MinION Nanopore sequencing increase the number of Next Generation Sequencing projects?</p>]]></description>
	<dc:creator>Strand</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/33917/webinar-on-leukocyte-immunobiology-helps-us-predict-post-operative-risk-using-pre-operative-markers-on-9-aug-8-am-pst</guid>
	<pubDate>Tue, 18 Jul 2017 08:21:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/33917/webinar-on-leukocyte-immunobiology-helps-us-predict-post-operative-risk-using-pre-operative-markers-on-9-aug-8-am-pst</link>
	<title><![CDATA[Webinar on Leukocyte immunobiology helps us predict post-operative risk using pre-operative markers on 9 Aug, 8 am PST]]></title>
	<description><![CDATA[<h2><strong><a href="http://www.strand-ngs.com/webinar_registration#registration-form">Free Live Webinar on Leukocyte immunobiology helps us predict post-operative risk using pre-operative markers on 9 Aug, 8 am PST</a></strong></h2><h2 id="Next-gen-seq"><em><a href="http://www.strand-ngs.com/webinar_registration">Speaker:</a></em></h2><p><strong>Mario Deng</strong><span>&nbsp;MD FACC FESC</span><br /><span>Professor of Medicine</span><br /><span>Advanced Heart Failure/Mechanical</span><br /><span>Support/Heart Transplant</span><br /><span>David Geffen School of&nbsp;</span><br /><span>Medicine at UCLA</span><br /><span>Ronald Reagan UCLA Medical Center</span></p><h2><em><a href="http://www.strand-ngs.com/webinar_registration">Abstract:</a></em></h2><div id="more-webinar"><p>Strand NGS supports a comprehensive and flexible RNA-Seq data analysis workflow consisting of Alignment, Quality Assessment, Filters, and a range of analysis and visualization options that help in studying a variety of samples and answering long-standing biological questions.</p></div><div><p>In this webinar, Dr. Deng will discuss the analysis of transcriptome, flow cytometry and cytokine data from pre-operative blood samples of advanced heart failure patients undergoing Mechanical Circulatory Support (MCS) surgery. He will discuss in detail the identification of prominent clinical variables, a set of transcriptome biomarkers, and their role in the context of systems biology. Finally, the application of Class Prediction algorithms in Strand NGS for identification of high-risk patients will be illustrated.</p><p>This immunobiology based study highlights the potential of machine learning techniques in clinical risk prediction and patient management, and from a clinician&rsquo; s perspective, the utility of biomarker discovery studies in helping patients make more informed decisions as a step towards personalized precision medicine.</p><p><em><a href="http://www.strand-ngs.com/webinar_registration#registration-form">Register here</a></em></p></div>]]></description>
	<dc:creator>Yeshodari</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/32253/webinar-on-fast-and-accurate-dna-variant-calling-on-26-apr-2017</guid>
	<pubDate>Fri, 21 Apr 2017 06:14:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/32253/webinar-on-fast-and-accurate-dna-variant-calling-on-26-apr-2017</link>
	<title><![CDATA[Webinar on Fast and Accurate DNA Variant Calling on 26 Apr 2017]]></title>
	<description><![CDATA[<p>Continuing our&nbsp;<a href="http://www.strand-ngs.com/webinar_registration">DNA-Seq webinar series</a>, we'll present Strand NGS v3.0 best-practices: a workflow that identifies highly accurate variants from raw reads. Our best practices workflow is twice as fast as its GATK counterpart, and results in precision/recall rates of up to 99%/98% on whole exome and whole genome samples. We'll also&nbsp;<a href="http://www.strand-ngs.com/webinar_registration">speak briefly</a>&nbsp;about some of the other features in v3.0 including one-shot pipelines, TSS plots, RNA-Seq performance improvements, and, for the first time, HGVS notations for SNP effect analysis.</p><p>Register here:&nbsp;<a href="http://www.strand-ngs.com/webinar_registration"></a><a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p>]]></description>
	<dc:creator>Yeshodari</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6458/bigre-lab</guid>
  <pubDate>Sun, 17 Nov 2013 10:35:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[BIGRE Lab]]></title>
  <description><![CDATA[
<p>The Laboratoire de Bioinformatique des Génomes et des Réseaux (Genome and Network Bioinformatics) is specialized in the conception, implementation, evaluation and application of bioinformatics approaches for the analysis of genome, transcriptome, proteome and metabolism.<br />Our main activities include</p>

<p>Analysis of regulatory sequences (RSAT project)<br />Classification and analysis of mobile genetic elements (ACLAME project).<br />Analysis of molecular interaction networks (NeAT project)<br />Inference of metabolic pathways from genomic and post-genomic data <br />(metabolic pathfinding, see also metabolic pathfinding in NeAT)<br />Critical assesment of protein interactions (CAPRI)</p>

<p>Lab Page http://www.bigre.ulb.ac.be/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36510/scallop-reference-based-transcriptome-assembler-for-rna-seq</guid>
	<pubDate>Tue, 08 May 2018 04:23:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36510/scallop-reference-based-transcriptome-assembler-for-rna-seq</link>
	<title><![CDATA[Scallop: reference-based transcriptome assembler for RNA-seq]]></title>
	<description><![CDATA[<p>Scallop is an accurate reference-based transcript assembler. Scallop features its high accuracy in assembling multi-exon transcripts as well as lowly expressed transcripts. Scallop achieves this improvement through a novel algorithm that can be proved preserving all phasing paths from reads and paired-end reads, while also achieves both transcripts parsimony and coverage deviation minimization.</p>
<p>Scallop paper has been published at&nbsp;<a href="https://www.nature.com/articles/nbt.4020"><span>Nature Biotechnology</span></a>. The datasets and scripts used in this paper to compare the performance of Scallop and other assemblers are available at&nbsp;<a href="https://github.com/Kingsford-Group/scalloptest"><span>scalloptest</span></a>.</p>
<p>Please also checkout the&nbsp;<span>podcast</span>&nbsp;about Scallop (thanks&nbsp;<a href="https://ro-che.info/">Roman Cheplyaka</a>&nbsp;for the interview). It is available at both&nbsp;<a href="https://bioinformatics.chat/scallop">the bioinformatics chat</a>&nbsp;and&nbsp;<a href="https://itunes.apple.com/us/podcast/the-bioinformatics-chat/id1227281398">iTunes</a>.</p>
<p>&nbsp;</p>
<p>https://github.com/Kingsford-Group/scallop</p><p>Address of the bookmark: <a href="https://github.com/Kingsford-Group/scallop" rel="nofollow">https://github.com/Kingsford-Group/scallop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences</guid>
	<pubDate>Tue, 18 Jun 2019 05:33:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences</link>
	<title><![CDATA[Cogent: a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences.]]></title>
	<description><![CDATA[<div id="yui_3_14_1_1_1560853173251_3865">Cogent is a tool that identifies gene&nbsp;families and reconstructs the coding genome using high-quality transcriptome data without a reference genome, and can be used to check&nbsp;assemblies&nbsp;for the presence of&nbsp;these known coding sequences.</div>
<div>&nbsp;</div>
<div>
<p>Cogent is a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences. It is designed to be used on&nbsp;<a href="https://github.com/PacificBiosciences/cDNA_primer/wiki">Iso-Seq data</a>&nbsp;and in cases where there is no reference genome or the ref genome is highly incomplete.</p>
<p>See a&nbsp;<a href="https://www.dropbox.com/s/mn6hwhguh0pqceu/20160106_Cogent_developers_conference_slides_Cuttlefish.pdf?dl=0">recent presentation</a>&nbsp;on Cogent being applied to the Cuttlefish Iso-Seq data.</p>
<p><a href="https://www.dropbox.com/s/kz0gi7qg0w82k9a/20161026_Cogent_manuscript_forGitHub.pdf?dl=0">Cogent preliminary draft paper (updated 2016Dec version)</a>,&nbsp;<a href="https://www.dropbox.com/s/37412o8glvnfhf9/20161026_Cogent_ManuscriptPlusSupplement_forGitHub.pdf?dl=0">Supplementary</a></p>
<p>Please see&nbsp;<a href="https://github.com/Magdoll/Cogent/wiki">wiki</a>&nbsp;for details on usage.</p>
</div><p>Address of the bookmark: <a href="https://github.com/Magdoll/Cogent" rel="nofollow">https://github.com/Magdoll/Cogent</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37813/evidentialgene-tr2aacds-mrna-transcript-assembly-software</guid>
	<pubDate>Mon, 01 Oct 2018 13:13:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37813/evidentialgene-tr2aacds-mrna-transcript-assembly-software</link>
	<title><![CDATA[EvidentialGene: tr2aacds, mRNA Transcript Assembly Software]]></title>
	<description><![CDATA[<p><span>Quality assessment of this mRNA Transcript Assembly Software is described in&nbsp;</span><a href="http://arthropods.eugenes.org/EvidentialGene/about/EvidentialGene_quality.html">EvidentialGene_quality</a><span>.</span></p>
<p>Too many transcript assemblies is much better than too few. It allows one then to apply biological criteria to pick out the best ones. Don't be misled by the "right number" of transcripts that one or other transcript assembler may produce. It is the "right sequence" you want, and now the only way to get it is to produce way too many assemblies on a good RNA data set, with several methods and several parameter settings.</p><p>Address of the bookmark: <a href="https://sourceforge.net/p/evidentialgene/blog/" rel="nofollow">https://sourceforge.net/p/evidentialgene/blog/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17515/ngs-online-training</guid>
  <pubDate>Sat, 27 Sep 2014 07:42:29 -0500</pubDate>
  <link></link>
  <title><![CDATA[NGS Online Training]]></title>
  <description><![CDATA[
<p>ArrayGen Technologies announces to provide online NGS training through out the globe. Now analyze your own NGS datasets from anywhere.For more information contact us at training@arraygen.com</p>

<p>Please visit our site at www.arraygen.com</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/26290/webinar-on-streamlining-large-scale-analysis-using-the-strand-ngs-pipeline-manager-on-24-feb-2016</guid>
	<pubDate>Fri, 05 Feb 2016 06:43:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/26290/webinar-on-streamlining-large-scale-analysis-using-the-strand-ngs-pipeline-manager-on-24-feb-2016</link>
	<title><![CDATA[Webinar on Streamlining large scale analysis using the Strand NGS Pipeline Manager on 24 Feb 2016]]></title>
	<description><![CDATA[<p><a href="http://www.strand-ngs.com/webinar_registration" title="webinar"><strong>Live Webinar on Streamlining large scale NGS data analysis using the Strand NGS Pipeline Manager on 24 Feb 2016</strong></a></p><p><strong>Abstract:</strong> Strand NGS includes comprehensive workflows for DNA-Seq, RNA-Seq, Small RNA-Seq, ChIP-Seq, MeDIP-Seq, and Methyl-Seq analysis. Each workflow includes a quality assessment and filter section, followed by a workflow-specific analysis section. The pipeline functionality in Strand NGS allows users to execute a sequence of analysis steps with specific parameters - all without any manual intervention. This simplifies the analysis in large scale sequencing projects where every sample needs to be processed identically.</p><p>In this webinar we will discuss the pre-packaged pipelines present in Strand NGS. The packaged pipelines have well-chosen default parameters and are suitable for users analyzing data for the first time in the tool. We will also show how advanced users can customize pipelines and share them with other Strand NGS users. Finally, we will show a brief glimpse of an elaborate pipeline that aligns reads, filters poor-quality matches, computes coverage metrics, identifies variants, checks for sample cross-contamination, and emails quality reports - all from within Strand NGS.</p><p><strong>Speaker:</strong> Dr. Vamsi Veeramachaneni, Vice President - Bioinformatics, Strand Life Sciences</p><p><strong>Details:</strong> Session 1: 2:30 PM IST, Session 2 : 10:30 PM IST<br /><strong>Register here:</strong> http://www.strand-ngs.com/webinar_registration</p><h3>&nbsp;</h3>]]></description>
	<dc:creator>Yeshodari</dc:creator>
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