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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/19631?offset=1020</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/17843/pathway-analysis</guid>
	<pubDate>Fri, 03 Oct 2014 08:51:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/17843/pathway-analysis</link>
	<title><![CDATA[Pathway Analysis]]></title>
	<description><![CDATA[<p>Pathway Analysis is usually performed with aim to enrich the genes with their functional information and reveal the underlying biological mechanisms pursue by genes. Pathway Analysis is not only limited to what biological pathways a particular set of expressed genes follow but also to disclose the relationships between these genes. With availability of more genomics, transcriptomics and proteomics data, interactions between genes involve in multiple pathways become more clear and also relationships between the genes, their transcripts, and their gene products. However, existing tools and dbs mainly based on knowledge driven approach in which pathways will be identified by finding the correlation between the&nbsp;<span>information in one of the pathway knowledge databases (KEGG,Reactome,Panther,BioCarta, Panther,GO,NCI,WikiPathways,etc) and gene expression result for a specific conditions for instance tumor, obesity , cold resistant crops/plants, etc.</span></p><p><span><strong>Introductory Articles/ppt/sources</strong>:</span></p><p><a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002375"><span>http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002375</span></a></p><p><a href="http://bioinformatics.mdanderson.org/MicroarrayCourse/Lectures09/Pathway%20Analysis.pdf"><span>http://bioinformatics.mdanderson.org/MicroarrayCourse/Lectures09/Pathway%20Analysis.pdf</span></a></p><p><a href="http://gettinggeneticsdone.blogspot.de/2012/03/pathway-analysis-for-high-throughput.html"><span>http://gettinggeneticsdone.blogspot.de/2012/03/pathway-analysis-for-high-throughput.html</span></a></p><p><a href="http://davetang.org/muse/tag/pathway/"><span>http://davetang.org/muse/tag/pathway/</span></a></p><p><a href="https://www.biostars.org/p/42219/"><span>https://www.biostars.org/p/42219/</span></a></p><p><a href="http://bioinformatics.ca//files/public/Pathways_2014_Module4_v2.pdf"><span>http://bioinformatics.ca//files/public/Pathways_2014_Module4_v2.pdf</span></a></p><p><a href="http://bioinformatics.ca//files/public/Pathways_2014_Module2.pdf"><span>http://bioinformatics.ca//files/public/Pathways_2014_Module2.pdf</span></a></p><p><span><strong>Impotant Database and Tools</strong>:</span></p><p>GeneMANIA, Cytoscape,&nbsp;<a href="http://www.ingenuity.com/products/ipa">IPA</a>&nbsp;and <a href="http://thomsonreuters.com/metacore/">Metacore</a> (Commerical ),&nbsp;<span>Pathway Commons, Reactome ,Panther, BioCyc, WikiPathways, Pathvisio, KEGG, NCI, Stringdb, Amigo,&nbsp;<span>WebGestalt ,<span>ConsensusPathDB ,GSEA,Blast2go</span></span></span></p><p><span><strong>Popular R based tools</strong>:</span></p><p><span>Reactome.db, ReactomePA, ClusterProfiler, Gage, SPIA, topGO, Pathview,DOSE,GOStat</span></p><p><span><strong>More</strong>:</span></p><p><a href="http://www.bioconductor.org/help/search/index.html?q=Enrichment+analysis+"><span>http://www.bioconductor.org/help/search/index.html?q=Enrichment+analysis+</span></a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<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/bookmarks/view/26587/last</guid>
	<pubDate>Wed, 09 Mar 2016 14:27:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26587/last</link>
	<title><![CDATA[LAST]]></title>
	<description><![CDATA[<p style="text-align: center;"><img src="http://last.cbrc.jp/lastwebfig.png" alt="sketch of  similar regions in sequences" style="border: 0px;"></p>
<p>LAST can:</p>
<ul>
<li>Handle <strong>big</strong> sequence data, e.g:
<ul>
<li>Compare two vertebrate genomes</li>
<li>Align billions of DNA reads to a genome</li>
</ul>
</li>
<li>Indicate the <a href="http://lastweb.cbrc.jp/about.html">reliability</a> of each aligned column.</li>
<li>Use sequence quality data <a href="http://nar.oxfordjournals.org/content/38/7/e100.abstract">properly</a>.</li>
<li>Compare DNA to proteins, with frameshifts.</li>
<li>Compare PSSMs to sequences</li>
<li>Calculate the likelihood of chance similarities between random sequences.</li>
<li>Do split and spliced alignment.</li>
<li><a href="http://last.cbrc.jp/doc/last-train.html">Train</a> alignment parameters for unusual kinds of sequence (e.g. nanopore).</li>
</ul><p>Address of the bookmark: <a href="http://last.cbrc.jp/" rel="nofollow">http://last.cbrc.jp/</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35437/dupradar-package</guid>
	<pubDate>Sun, 04 Feb 2018 14:28:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35437/dupradar-package</link>
	<title><![CDATA[dupRadar package]]></title>
	<description><![CDATA[<p><span>The&nbsp;</span><em>dupRadar</em><span>&nbsp;package gives an insight into the duplication problem by graphically relating the gene expression level and the duplication rate present on it. Thus, failed experiments can be easily identified at a glance</span></p><p>Address of the bookmark: <a href="https://bioconductor.org/packages/3.7/bioc/vignettes/dupRadar/inst/doc/dupRadar.html" rel="nofollow">https://bioconductor.org/packages/3.7/bioc/vignettes/dupRadar/inst/doc/dupRadar.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26827/kamaleshwar-singh-lab</guid>
  <pubDate>Fri, 25 Mar 2016 10:46:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[Kamaleshwar Singh Lab]]></title>
  <description><![CDATA[
<p>The focus of Dr. Singh’s research and teaching is on the molecular mechanistic basis for environmental carcinogen-induced genetic (DNA damage) and epigenetic changes, and susceptibility to human cancer development</p>

<p>More at http://www.tiehh.ttu.edu/dr.-kamaleshwar-singh.html</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26435/bioinformatics-centre-bose-institute-vacancy-of-research-associate-senior-research-fellow</guid>
  <pubDate>Mon, 22 Feb 2016 03:27:17 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Centre, Bose Institute vacancy of Research Associate / Senior Research Fellow]]></title>
  <description><![CDATA[
<p>Bioinformatics Centre, Bose Institute vacancy of Research Associate / Senior Research Fellow</p>

<p>Location where with post of Research Associate / Senior Research Fellow is available:<br />Bioinformatics Centre, Bose Institute in Kolkata, West Bengal</p>

<p>Title of the Project: "Setting up of National Facility on Interactive Graphics Computer System".</p>

<p>No. of the Post: 01 One</p>

<p>Salary: Rs. 22000/- per month plus admissible HRA and Medical Benefits for RA and Rs. 20000/- per month plus admissible HRA and Medical Benefits for SRF (Extended).</p>

<p>Age Limit: Max. 35 years for RA and Max. 33 years for SRF (Extended)</p>

<p>Required Job Profile:</p>

<p>Candidate must possess PhD degree in biological or chemical sciences with in depth understanding of protein structure and function; experience on protein crystallization and various modeling software will be advantages and candidate who have submitted PhD thesis can be considered as extended SRF.</p>

<p>The project would involve cloning, expression, crustallization of vibrio cholera toxin, Ace and modeling of its admissible HRA and medical benefits for SRF (Extended).</p>

<p>How to apply:</p>

<p>Eligible and interested candidates should need to appear before the selection committee along with typed application addressed to the above mentioned address along with biodata with complete details and attested copies of certificates on 02.03.2016 at 11:30 am. No TA or DA will be paid for attending the interview. No TA or DA will be paid for attending the interview.</p>

<p>Refer to http://www.boseinst.ernet.in/ADVT/15/p_30.pdf</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25781/bioinformatics-trainee-at-university-of-kalyani</guid>
  <pubDate>Tue, 22 Dec 2015 01:51:42 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Trainee at University of Kalyani]]></title>
  <description><![CDATA[
<p>Bioinformatics Trainee<br />Eligibility : MSc<br />Location : Kolkata<br />Last Date : 28 Dec 2015<br />Hiring Process : Walk - In<br />University of Kalyani </p>

<p>Bioinformatics Trainee Job position in University of Kalyani<br />Number of Posts :  02 <br />Qualification : M.Sc. in any branch of life science with prior knowledge of Bioinformatics <br />Fellowship / Stipend / Salary : As per DBT rules <br />Duration of the Post :  Six months starting from January, 2016 <br />How to apply<br />Walk-in-interview will be held on 28.12.2015 at Department of Biochemistry and Biophysics, University of Kalyani.</p>

<p>More at http://www.klyuniv.ac.in/index.php/recruitments</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/25987/chekulaevalab</guid>
  <pubDate>Tue, 12 Jan 2016 02:32:03 -0600</pubDate>
  <link></link>
  <title><![CDATA[Chekulaevalab]]></title>
  <description><![CDATA[
<p>Focusing on understanding the molecular mechanisms that regulate mRNA translation, localization and stability and role of non-coding RNAs in this process. Up to 90% of human DNA is estimated to be transcribed into so called non-coding RNAs that are not translated into proteins. Many of them act as potent modifiers of gene expression. miRNAs are a class of such short non-coding RNAs. They regulate expression of more than a half of eukaryotic genes, thus, affecting multiple biological processes, including cell proliferation, differentiation, apoptosis and senescence. Not surprisingly, miRNAs are involved in many human pathologies, including cancer and neurological disorders and hold great potential as drug targets, disease markers, as well as therapeutic agents.<br />Our lab is located at the Berlin Institute for Medical Systems Biology (BIMSB), a part of the Max Delbrück Center for Molecular Medicine (MDC).</p>

<p>http://www.chekulaevalab.org/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26356/spines</guid>
	<pubDate>Tue, 09 Feb 2016 05:07:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26356/spines</link>
	<title><![CDATA[Spines]]></title>
	<description><![CDATA[<div id="content-header">
<h1>Spines</h1>
</div>
<div id="node-1301">
<div>
<div>
<p><a href="http://www.broadinstitute.org/ftp/distribution/software/spines/"><em>Spines</em></a> is a collection of software tools, developed and used by the Vertebrate Genome Biology Group at the Broad Institute. It provides basic data structures for efficient data manipulation (mostly genomic sequences, alignments, variation etc.), as well as specialized tool sets for various analyses. It also features three sequence alignment packages: <em>Satsuma,</em> a highly parallelized program for high-sensitivity, genome-wide synteny; <em>Papaya,</em> an all-purpose alignment tool for less diverged sequences; and <em>SLAP,</em> a context-sensitive local aligner for diverged sequences with large gaps.</p>
<p>Access <em>Spines</em> <a href="http://www.broadinstitute.org/ftp/distribution/software/spines/">here</a>.</p>
</div>
</div>
</div>
<p>http://www.broadinstitute.org/science/programs/genome-biology/spines</p><p>Address of the bookmark: <a href="http://www.broadinstitute.org/science/programs/genome-biology/spines" rel="nofollow">http://www.broadinstitute.org/science/programs/genome-biology/spines</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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