<?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/40204?offset=1140</link>
	<atom:link href="https://bioinformaticsonline.com/related/40204?offset=1140" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26378/centurion</guid>
	<pubDate>Fri, 12 Feb 2016 04:45:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26378/centurion</link>
	<title><![CDATA[Centurion]]></title>
	<description><![CDATA[<p>Although centromeres are essential for life and are the subject of extensive research, centromere locations in yeast genomes are difficult to infer, and in most species they are still unknown. Recently, the chromatin conformation assay Hi-C has been re-purposed for diverse applications, including de novo genome assembly, deconvolution of metagenomic samples, and inference of centromere locations. We describe a method, Centurion, that jointly infers the locations of all centromeres in a single yeast genome by exploiting the centromeres&rsquo; tendency to cluster in 3D space. We first demonstrate the accuracy of Centurion in identifying known centromere locations from high coverage Hi-C data of budding yeast and a human malaria parasite. We then use two metagenomic samples with relatively low coverage Hi-C data to infer centromere locations for each chromosome in 14 different yeast species. For yeasts with large centromeres (e.g., S. pombe) Centurion predicts the exact centromere locations. For seven yeasts with point centromeres, Centurion predicts most of the centromeres at an average of 5~kb distance from their known locations. Finally, we predict centromere coordinates for six yeast species that currently lack centromere annotations. These results suggest that Centurion can be used for centromere identification for a large number of yeast species, even with a limited amount of Hi-C sequencing.</p>
<p>Paper:http://www.ncbi.nlm.nih.gov/pubmed/25940625</p>
<p>More at http://cbio.ensmp.fr/centurion/</p><p>Address of the bookmark: <a href="http://cbio.ensmp.fr/centurion/" rel="nofollow">http://cbio.ensmp.fr/centurion/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26391/radka-reifova-lab</guid>
  <pubDate>Mon, 15 Feb 2016 06:00:48 -0600</pubDate>
  <link></link>
  <title><![CDATA[Radka Reifová Lab]]></title>
  <description><![CDATA[
<p>We are generally interested in the mechanisms of species origin from a molecular and ecological perspective. Particularly, we are interested in the role of sex chromosomes in speciation. Most of our research is done on birds and mammals. Currently, we focus our research on two hybridizing song birds, the Common nightingale (Luscinia megarhynchos) and the Thrush Nightingale (L. luscinia). Combining population genomic and ecological approaches we try to elucidate the genetic architecture of reproductive isolation and understand the role of interspecific competition and song convergence in the evolution of reproductive isolation between the species. </p>

<p>More at http://web.natur.cuni.cz/~radkas/index.php?page=research</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26426/genome-browser-gbrowse</guid>
	<pubDate>Fri, 19 Feb 2016 09:22:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26426/genome-browser-gbrowse</link>
	<title><![CDATA[Genome Browser : GBrowse]]></title>
	<description><![CDATA[<p>Generic Genome Browser Version 2: A Tutorial for Administrators</p>
<p>This is an extensive tutorial to take you through the main features and gotchas of configuring GBrowse as a server. This tutorial assumes that you have successfully set up Perl, GD, BioPerl and the other GBrowse dependencies. If you haven't, please see the <a href="http://gmod.org/wiki/GBrowse_2.0_HOWTO">GBrowse HOWTO</a> During most of the tutorial, we will be using the "in-memory" GBrowse database (no relational database required!) Later we will show how to set up a genome size database using the berkeleydb and MySQL adaptors.</p>
<p>More at http://elp.ucdavis.edu/tutorial/tutorial.html</p><p>Address of the bookmark: <a href="http://elp.ucdavis.edu/tutorial/tutorial.html" rel="nofollow">http://elp.ucdavis.edu/tutorial/tutorial.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</guid>
	<pubDate>Mon, 29 Feb 2016 17:39:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</link>
	<title><![CDATA[scikit-learn]]></title>
	<description><![CDATA[<p>Machine Learning in Python</p>
<p>Simple and efficient tools for data mining and data analysis<br> Accessible to everybody, and reusable in various contexts<br> Built on NumPy, SciPy, and matplotlib<br> Open source, commercially usable - BSD license</p>
<p>More at&nbsp;http://scikit-learn.org/stable/index.html</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://scikit-learn.org/stable/auto_examples/index.html" rel="nofollow">http://scikit-learn.org/stable/auto_examples/index.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26927/phylographer-graph-visualization-tool</guid>
	<pubDate>Wed, 06 Apr 2016 19:06:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26927/phylographer-graph-visualization-tool</link>
	<title><![CDATA[PhyloGrapher - Graph Visualization Tool]]></title>
	<description><![CDATA[<p><strong>PhyloGrapher</strong><span>&nbsp;is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).</span><strong>PhyloGrapher</strong><span>&nbsp;is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;to visualize any type of relations between elements.&nbsp;</span></p>
<p><span>More at&nbsp;http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</span></p><p>Address of the bookmark: <a href="http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html" rel="nofollow">http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27225/painless-package-development-for-r</guid>
	<pubDate>Tue, 03 May 2016 05:31:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27225/painless-package-development-for-r</link>
	<title><![CDATA[Painless package development for R]]></title>
	<description><![CDATA[<p>Devtools makes package development a breeze: it works with R&rsquo;s existing conventions for code structure, adding efficient tools to support the cycle of package development. With devtools, developing a package becomes so easy that it will be your default layout whenever you&rsquo;re writing a significant amount of code.</p>
<p>Before you get started be sure to check out:</p>
<ul>
<li><a href="https://groups.google.com/forum/#%21forum/rdevtools" title="Google devtools Group">devtools Google Group &ndash;&nbsp;https://groups.google.com/forum/#!forum/rdevtools</a></li>
<li><a href="http://adv-r.had.co.nz/" title="Hadley W Online Book">book on &ldquo;Advanced R programming&rdquo; &ndash;&nbsp;http://adv-r.had.co.nz/</a></li>
<li><a href="https://github.com/hadley/devtools" title="devtools GitHub">GitHub repository &ndash;&nbsp;https://github.com/hadley/devtools</a></li>
</ul>
<h3 id="getting_started">&nbsp;</h3><p>Address of the bookmark: <a href="https://www.rstudio.com/products/rpackages/devtools/" rel="nofollow">https://www.rstudio.com/products/rpackages/devtools/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<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>
</item>

<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>
</item>
<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>
</item>

</channel>
</rss>