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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27465?offset=1020</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27238/slurm</guid>
	<pubDate>Wed, 04 May 2016 05:13:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27238/slurm</link>
	<title><![CDATA[SLURM]]></title>
	<description><![CDATA[<p><a href="http://www.schedmd.com/">SLURM</a> workload manager software, a free open-source workload manager designed specifically to satisfy the demanding needs of high performance computing.</p>
<p>This page is a <em>HOWTO</em> guide for setting up a <a href="http://www.schedmd.com/">SLURM</a> installation, currently focused on a CentOS 7 Linux OS. Please send feedback to Ole.H.Nielsen /at/ fysik.dtu.dk.</p>
<p>See the <a href="http://www.schedmd.com/">SLURM</a> homepage (also <a href="https://computing.llnl.gov/linux/slurm/">https://computing.llnl.gov/linux/slurm/</a>).</p><p>Address of the bookmark: <a href="https://wiki.fysik.dtu.dk/niflheim/SLURM" rel="nofollow">https://wiki.fysik.dtu.dk/niflheim/SLURM</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27290/scientists-post-at-monsanto</guid>
  <pubDate>Wed, 11 May 2016 07:58:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[Scientists post at Monsanto]]></title>
  <description><![CDATA[
<p>Sustainable agriculture is at the core of Monsanto. We develop technologies that enable farmers to produce more crops while conserving natural resources. Monsanto scientists are conducting research and development (R&amp;D) to revolutionize plant breeding and biotechnology.</p>

<p>Monsanto is seeking a very talented Genomics Scientistto become an integral member of our Global Pipeline Analytics team with a focus on quantitative genetics. The ideal candidate will have familiarity with modeling and analysis of genetic data sets using a variety of statistical techniques.</p>

<p>Major Responsibilities:<br />- Provide guidance on experimental design for genomic-related experiments<br />- Familiarity with analysis of the following methods: GWS, QTL, eQTL, RNA-Seq<br />- Provide written and oral presentations of methods, results, conclusions, and recommendations to peer and management groups.<br />- Ensure timely delivery and clear communication of results<br />- Develop strong and successful collaborations among various Monsanto enabling teams.</p>

<p>Required Skills:</p>

<p>- PhD degree in Statistics, Biostatistics, Statistical Genetics, Quantitative Genetics, Breeding, Bioinformatics or a related field with 2 years of experience<br />- Working knowledge and experience with one of the following quantitative languages:R, Python, Perl, SAS<br />- Background in Windows and Linux operating systems<br />- Very strong problem solving skills will be required to work well as a member of a dynamic team<br />- Strong verbal and written communication skills.<br />- Demonstrated ability to deliver timely results and be results oriented.<br />- Extensive knowledge of quantitative genetics and experimental design.&nbsp;<br />- Demonstrated track record of solving challenging and complex problems.</p>

<p>Desired Skills/Experience:</p>

<p>- Excellent communication skills, with the ability to summarize complex concepts in language understandable by scientists from a variety of disciplines.<br />- Experience in agronomy and/or plant breeding in vegetables or row crops.</p>

<p>Please apply to<br />https://jobs.monsanto.com/job/st-louis/genomics-scientist/769/2081771</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/27318/sample-binc-question-paper-2016-part2</guid>
	<pubDate>Fri, 13 May 2016 03:42:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/27318/sample-binc-question-paper-2016-part2</link>
	<title><![CDATA[Sample BINC question paper 2016 - part2]]></title>
	<description><![CDATA[<p>Download the sample question paper for BINC 2016 - paer II</p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/27318" length="52024" type="application/pdf" />
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27331/andi</guid>
	<pubDate>Fri, 13 May 2016 05:16:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27331/andi</link>
	<title><![CDATA[Andi]]></title>
	<description><![CDATA[<p>This is the <code>andi</code> program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because <code>andi</code> does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.</p>
<p>This readme covers all necessary instructions for the impatient to get <code>andi</code> up and running. For extensive instructions please consult the <a href="https://github.com/EvolBioInf/andi/blob/master/andi-manual.pdf">manual</a>.</p>
<p>More at https://github.com/evolbioinf/andi/</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27475/polyphen-2-prediction-of-functional-effects-of-human-nssnps</guid>
	<pubDate>Mon, 23 May 2016 02:27:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27475/polyphen-2-prediction-of-functional-effects-of-human-nssnps</link>
	<title><![CDATA[PolyPhen-2: Prediction of functional effects of human nsSNPs]]></title>
	<description><![CDATA[<p><strong>PolyPhen-2</strong> (<strong>Poly</strong>morphism <strong>Phen</strong>otyping v<strong>2</strong>) is a tool which predicts possible impact of an amino acid substitution on the structure and function of a human protein using straightforward physical and comparative considerations.</p><p>Address of the bookmark: <a href="http://genetics.bwh.harvard.edu/pph2/" rel="nofollow">http://genetics.bwh.harvard.edu/pph2/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27432/gkno</guid>
	<pubDate>Fri, 20 May 2016 18:56:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27432/gkno</link>
	<title><![CDATA[GKNO]]></title>
	<description><![CDATA[<p><span>gkno opens the world of complex bioinformatic analysis to people of all level of computational expertise. This site contains documentation, tutorials and information on all the tools that comprise gkno.</span></p>
<p><span>http://gkno.me/how-to/install.html</span></p>
<p><span>http://gkno.me/software.html</span></p><p>Address of the bookmark: <a href="http://gkno.me/" rel="nofollow">http://gkno.me/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27479/biogps</guid>
	<pubDate>Mon, 23 May 2016 03:15:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27479/biogps</link>
	<title><![CDATA[BioGPS]]></title>
	<description><![CDATA[<p>A free&nbsp;<em>extensible</em>&nbsp;and&nbsp;<em>customizable</em>&nbsp;<strong>gene annotation portal</strong>, a complete resource for learning about&nbsp;<strong>gene and protein function</strong>.</p>
<p>http://biogps.org/#goto=welcome</p><p>Address of the bookmark: <a href="http://biogps.org/#goto=welcome" rel="nofollow">http://biogps.org/#goto=welcome</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27679/cluego</guid>
	<pubDate>Thu, 02 Jun 2016 09:51:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27679/cluego</link>
	<title><![CDATA[ClueGO]]></title>
	<description><![CDATA[<p>ClueGO is a Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network and it can be used in combination with GOlorize.</p><p>Address of the bookmark: <a href="http://www.ici.upmc.fr/cluego/" rel="nofollow">http://www.ici.upmc.fr/cluego/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27696/methylkit</guid>
	<pubDate>Fri, 03 Jun 2016 10:09:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27696/methylkit</link>
	<title><![CDATA[methylKit]]></title>
	<description><![CDATA[<p><em>methylKit</em> is an <a href="http://en.wikipedia.org/wiki/R_%28programming_language%29">R</a> package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing. The package is designed to deal with sequencing data from <a href="http://www.nature.com/nprot/journal/v6/n4/abs/nprot.2010.190.html">RRBS</a> and its variants, but also target-capture methods such as <a href="http://www.halogenomics.com/sureselect/methyl-seq">Agilent SureSelect methyl-seq</a>. In addition, methylKit can deal with base-pair resolution data for 5hmC obtained from Tab-seq or oxBS-seq. It can also handle whole-genome bisulfite sequencing data if proper input format is provided.</p><p>Address of the bookmark: <a href="https://github.com/al2na/methylKit" rel="nofollow">https://github.com/al2na/methylKit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28269/4dgenome</guid>
	<pubDate>Mon, 04 Jul 2016 00:44:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28269/4dgenome</link>
	<title><![CDATA[4DGenome]]></title>
	<description><![CDATA[<p><span>Records in 4DGenome are compiled through comprehensive literature curation of experimentally-derived and computationally-predicted interactions. The current release contains 4,433,071 experimentally-derived and 3,605,176 computationally-predicted interactions in 5 organisms. Experimental data cover both high throughput datasets and individiual focused studies.&nbsp;</span><br><br><span>All interaction data are freely available in a standardized file format. Records can be queried by genomic regions, gene names, organism, and detection technology.&nbsp;</span></p><p>Address of the bookmark: <a href="http://4dgenome.research.chop.edu/" rel="nofollow">http://4dgenome.research.chop.edu/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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