<?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/27257?offset=100</link>
	<atom:link href="https://bioinformaticsonline.com/related/27257?offset=100" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data</guid>
	<pubDate>Wed, 23 Jul 2014 07:29:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data</link>
	<title><![CDATA[COSMOS, our workflow management system for NGS data]]></title>
	<description><![CDATA[<p><strong>COSMOS</strong>, our Python-based management system for implementing large-scale parallel workflows focusing on, but not restricted to, large-scale short-read "NGS" sequencing data is open-access published via <a href="http://bioinformatics.oxfordjournals.org/content/early/2014/06/29/bioinformatics.btu385.abstract">Advance Access</a> in <em>Bioinformatics</em> (<a href="http://scholar.harvard.edu/lancaster/publications/cosmos-python-library-massively-parallel-workflows">Gafni et al. 2014</a>).&nbsp; It is also available for download for non-commercial academic and research purposes at:</p>
<p><strong>&nbsp;<a href="http://cosmos.hms.harvard.edu/">http://cosmos.hms.harvard.edu/</a></strong>.</p><p>Address of the bookmark: <a href="https://cosmos.hms.harvard.edu/" rel="nofollow">https://cosmos.hms.harvard.edu/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/14756/roderic-guigo-lab</guid>
  <pubDate>Mon, 01 Sep 2014 17:13:00 -0500</pubDate>
  <link></link>
  <title><![CDATA[Roderic Guigó Lab]]></title>
  <description><![CDATA[
<p>Research in our group focuses on the investigation of the signals involved in gene specification in genomic sequences (promoter elements, splice sites, translation initiation sites, etc…). We are interested both in the mechanism of their recognition and processing, and in their evolution. In addition, but related to this basic component of our research, our group is also involved in the development of software for gene prediction and annotation in genomic sequences. Our group also actively participates in the analysis of many eukaryotic genomes and it in involved in the NIH-funded ENCODE project. Furthermore we are members of two large cancer-studies consortia (chronic lymphocytic leukemia "CLL" and Breast Cancer -Hospital del Mar/CRG/Roche-).  <br /> <br />More at http://big.crg.cat/computational_biology_of_rna_processing</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/15000/which-mathstatistics-programming-languageapplication-do-you-most-frequently-use-in-bioinformatics</guid>
	<pubDate>Thu, 04 Sep 2014 17:46:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/15000/which-mathstatistics-programming-languageapplication-do-you-most-frequently-use-in-bioinformatics</link>
	<title><![CDATA[Which math/statistics programming language/application do you most frequently use in bioinformatics?]]></title>
	<description><![CDATA[<p>I'm doing a bit more statistical analysis on some bioinformatics things lately, and I'm curious if there are any programming languages that are particularly good for this NGS computation. What suggestions do you guys have? Are there any languages that have exceptionally good libraries?</p>]]></description>
	<dc:creator>John Parker</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19187/srbioinformatics-analyst-ngs-at-ocimum-biosolution</guid>
  <pubDate>Sat, 15 Nov 2014 04:46:10 -0600</pubDate>
  <link></link>
  <title><![CDATA[Sr.Bioinformatics Analyst (NGS) at Ocimum Biosolution]]></title>
  <description><![CDATA[
<p>“Ocimum Biosolution” is a comprehensive Integrated Life Science Informatics solutions provider with service offerings that span Sample and Data Management (LIMS, Biologics Data Management), Genomics Data Analysis Services such as Gene Expression, Genotyping, and Next Gen Sequencing, Bioinformatics and Genomics Databases (BioExpress®, ToxExpress®) and Bio-IT consulting services.</p>

<p>Experience Required: 3-5 years of experience</p>

<p>No of Positions : Multiple</p>

<p>Qualifications: Candidates with minimum qualification as M.Sc Bioinformatics with 3-5  years of experience in Life sciences R&amp;D or Pharma Industry.</p>

<p>Ph.D candidates with research experience in Bioinformatics with publications in International journal and minimum 2 years of  industry experience in clinical genomics will be preferred for this position.</p>

<p>Requirement:</p>

<p>1.  Must have basic understanding of molecular biology and Genomics.</p>

<p>2. Experience in application development or must have expertise in programming using either of Perl/Python.</p>

<p>3.  Experience in statistical programming using R/Bioconductor/Matlab.</p>

<p>4. Strong concept in statistical and mathematical modelling.</p>

<p>5.  Experience in designing and developing the bioinformatics pipeline.</p>

<p>6.  Must have minimum 2+ years of hands on experience in NSG data analysis such as RNA-Seq,Exome-Seq ,Chip-Seq and downstream analysis.</p>

<p>7. Knowledge in WGS ,WES, Targeted re-sequencing,GWAS and population genomics will be preferred.</p>

<p>8. Must have experience working on opensource software/Framework and commercial software for NGS data analysis and reporting.</p>

<p>9. Should be aware of handling big data and guiding team members on multiple projects simultaneously.</p>

<p>10. Should have experience coordinating with different groups of clinical research scientist for various project requirements.</p>

<p>11. Ability to work as team as well as independently with minimal support.</p>

<p>More at http://www.ocimumbio.com/careers1/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome</guid>
	<pubDate>Fri, 12 Dec 2014 22:27:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome</link>
	<title><![CDATA[A 3D Map of the Human Genome]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/dES-ozV65u4" frameborder="0" allowfullscreen></iframe>Suhas Rao and Miriam Huntley (of the Aiden Lab) describe a 3D map of the human genome at kilobase resolution, revealing the principles of chromatin looping. Guest Origami Folding: Sarah Nyquist.

Suhas S.P. Rao*, Miriam H. Huntley*, Neva C. Durand, Elena K. Stamenova, Ivan D. Bochkov, James T. Robinson, Adrian L. Sanborn, Ido Machol, Arina D. Omer, Eric S. Lander, Erez Lieberman Aiden. (2014). A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping. Cell.]]></description>
	
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/19979/zhang-lab</guid>
  <pubDate>Sun, 28 Dec 2014 12:43:08 -0600</pubDate>
  <link></link>
  <title><![CDATA[Zhang Lab]]></title>
  <description><![CDATA[
<p>We develop and use integrative bioinformatics approaches to extract biological meanings from experimental data and generate hypotheses for experimental validation. Please explore our website to learn more about our people and our research.</p>

<p>More at http://bioinfo.vanderbilt.edu/zhanglab/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22403/ryan-e-mills-lab</guid>
  <pubDate>Tue, 26 May 2015 09:29:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Ryan E. Mills Lab]]></title>
  <description><![CDATA[
<p>Our research group is primarily focused on the analysis of whole genome sequence data to identify genetic variation (primarily structural variation) and examine their potential functional impact in disease phenotypes. We are particularly interested in analyzing complex regions of the genome that are not easily resolved through modern sequencing approaches and which may exhibit interesting mechanistic origins.</p>

<p>We are also interested in the large-scale integration of genomic, expression, methylation and proteomic data sets, as well as the application of whole genome sequence analysis in clinical diagnostics. </p>

<p>More at http://millslab.ccmb.med.umich.edu/index.html</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/23149/raphael-lab</guid>
  <pubDate>Sat, 04 Jul 2015 19:05:29 -0500</pubDate>
  <link></link>
  <title><![CDATA[Raphael Lab]]></title>
  <description><![CDATA[
<p>Raphael Lab research is focused on Bioinformatics and Computational Biology.</p>

<p>Current research interests include next-generation DNA sequencing, structural variation, genome rearrangements in cancer and evolution, and network analysis of somatic mutations in cancer. Earlier research included topics in comparative genomics, multiple sequence alignment, and motif finding.</p>

<p>More athttp://compbio.cs.brown.edu/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/23633/biorg</guid>
  <pubDate>Tue, 04 Aug 2015 20:52:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[BioRG]]></title>
  <description><![CDATA[
<p>This research group works on problems from the fields of Bioinformatics, Biotechnology, Data Mining, and Information Retrieval. The group's research projects includes Comparative Genomics of Bacterial genomes, Metagenomics, Genomic databases, Pattern Discovery in sequences and structures, micro-array data analysis, prediction of regulatory elements, primer design, probe design, phylogenetic analysis, medical image processing, image analysis, data integration, data mining, information retrieval, knowledge discovery in electronic medical records, and more. </p>

<p>More at http://biorg.cis.fiu.edu/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25284/rajiv-gandhi-centre-for-biotechnology-rgcb-invites-applications-for-the-following-three-faculty-scientist</guid>
  <pubDate>Tue, 24 Nov 2015 22:13:16 -0600</pubDate>
  <link></link>
  <title><![CDATA[Rajiv Gandhi Centre for Biotechnology (RGCB) invites applications for the following three faculty scientist]]></title>
  <description><![CDATA[
<p>Scientist Positions<br />Advt. No.RGCB Advt./SCI 2015/1<br /> <br />November 11, 2015</p>

<p>Rajiv Gandhi Centre for Biotechnology (RGCB) invites applications for the following three faculty scientist positions:</p>

<p>Scientist E-II or F in Bioinformatics &amp; Computational Biology</p>

<p>SCIENTIST E-II OR F IN COMPUTATIONAL BIOLOGY &amp; BIOINFORMATICS</p>

<p>Highly motivated and innovative individual who will pursue basic research, solve biological problems with emphasis on computational and quantitative experimental methods and build active bridges to translational research. The scientist will also provide computational biology support to ongoing research programs in disease biology, provide assistance to analyze complex data sets generated by RGCB scientists and collaborators inclusive of including high dimensional “omics” data and next generation sequencing data, such as whole genome, exome, RNA-seq and ChIP-seq as well as provide leadership for high quality training for junior scientists and regular teaching programs of the institute. Areas of research of interest to RGCB include but are not limited to computational, systems, or quantitative biology with applications to cell biology, developmental biology, metabolism, genomics, proteomics, biophysics, biological information systems, network pharmacology, drug design and cancer research. The scientist’s responsibilities include efforts for the integration of DNA variant annotation with statistical genetic analysis methods including linkage, imputation and association methods, adopting novel and innovative methodologies to analyze, integrate and interpret high dimensional data sets, provision of annotation to robust genetics and genomics findings using several data sources and methods, data management of exploratory clinical and R&amp;D studies in partnership with other lines of genetic data generated from internal and external studies, delivery and documentation of genomic information to support genetic studies, ensuring high-quality genetic and genomic data is incorporated into exploratory- clinical research programs, developing tools that make maximum use of multiple data sources to support annotation of DNA variation and contributes to systems biology initiatives within RGCB </p>

<p>More at http://rgcb.res.in/scientist-positions/</p>

<p>Application Form http://rgcb.res.in/wp-content/uploads/2015/11/APPLICATION-FORMAT-FOR-SCIENTISTS.docx</p>
]]></description>
</item>

</channel>
</rss>