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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26925?offset=780</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26414/advanced-bash-scripting-guide</guid>
	<pubDate>Thu, 18 Feb 2016 04:50:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26414/advanced-bash-scripting-guide</link>
	<title><![CDATA[Advanced Bash-Scripting Guide]]></title>
	<description><![CDATA[<p>This tutorial assumes no previous knowledge of scripting or programming, yet progresses rapidly toward an intermediate/advanced level of instruction <em>. . . all the while sneaking in little nuggets of <span>UNIX</span>&reg; wisdom and lore</em>. It serves as a textbook, a manual for self-study, and as a reference and source of knowledge on shell scripting techniques. The exercises and heavily-commented examples invite active reader participation, under the premise that <tt><strong>the only way to really learn scripting is to write scripts</strong></tt>.</p>
<p>This book is suitable for classroom use as a general introduction to programming concepts.</p>
<p>More at http://tldp.org/LDP/abs/html/</p><p>Address of the bookmark: <a href="http://tldp.org/LDP/abs/html/" rel="nofollow">http://tldp.org/LDP/abs/html/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26438/scientist-at-regional-medical-research-centre-icmr-rmrc-port-blair</guid>
  <pubDate>Mon, 22 Feb 2016 04:38:48 -0600</pubDate>
  <link></link>
  <title><![CDATA[Scientist at Regional Medical Research Centre (ICMR), RMRC, Port Blair]]></title>
  <description><![CDATA[
<p>Scientist</p>

<p>Eligibility : MSc, M Phil / Phd, BE/B.Tech</p>

<p>Location : Delhi</p>

<p>Last Date : 08 Mar 2016</p>

<p>Hiring Process : Walk - In<br />Regional Medical Research Centre - </p>

<p>Notification Order No.1-51/Proj/RMRC/PB/</p>

<p>Scientist – II (Post Code: BIC-II) job position in Regional Medical Research Centre (ICMR)</p>

<p>Essential Qualification: 1 st class Master’s degree in Bioinformatics / Computational Biology.  B.E / B.Tech (Bioinformatics / Computer Science / Biotechnology) OR 2nd Class M.Sc. with Ph.D. in Bioinformatics / Computational Biology / Life Science.</p>

<p>Desirable Qualification:  Post-doctoral research experience in Bioinformatics / Computational Biology / Computer Science / Life Science at a recognized institution.  Experience in handling and analyzing sequencing data.  Experience in scripting languages (PERL/PYTHON) etc./ Statistical software.  Experience in developing research projects.</p>

<p>Number of Post: 1 UR</p>

<p>Place of Posting: RMRC, Port Blair </p>

<p>Age Limit: 40 years</p>

<p>Pay Scale : Rs.45,954<br />How to apply</p>

<p>Interested candidates are invited to submit applications along with copies of all the certificates of educational qualifications, date of birth, working experience etc . on the affixing a passport size photograph by Application Format to attend a walk-in interview on 8th March 2016 at 10:30 AM.</p>

<p>More at http://www.icmr.nic.in/icmrnews/port%20blair%20Bioinf%2003-2016.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26562/jrf-at-icgeb</guid>
  <pubDate>Fri, 04 Mar 2016 05:34:42 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF at ICGEB]]></title>
  <description><![CDATA[
<p>Vacancy Notice PU/TS/01-16</p>

<p>JRF jobs in International Centre for Genetic Engineering and Biotechnology</p>

<p>Area of research: Computational analysis of protein-protein interactions and metabolic reconstruction of pathways</p>

<p>Qualification : Suitable candidate must have completed Masters in Computer Science/Physics/Mathematics/Bioinformatics or PG diploma in Bioinformatics with very sound programming skills shown in the form of completed project or paper. Programming Skill required: Java/perl/python or any other scripting language and working knowledge of MySQL. Candidate should have some familiarity with R statistical package.</p>

<p>The salary will be as per the guidelines of DBT/DST, based on qualification and experience.</p>

<p>How to apply</p>

<p>Interested candidates may send application along with CV via email to hemant@icgeb.res.in  (Dr. Hemant Ritturaj Kushwaha) on or before 08/03/2016. Candidates applying through Email must mention “Application for JRF” in their subject line.</p>

<p>More at http://www.icgeb.org/vacancies.html</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/44365/program-officer-bioinformatics-at-jhpiego</guid>
  <pubDate>Tue, 29 Aug 2023 00:05:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Program Officer, Bioinformatics at Jhpiego]]></title>
  <description><![CDATA[
<p>Jhpiego is a non-profit global health leader and Johns Hopkins University affiliate that is saving lives, improving health, and transforming futures. We partner with governments, health experts, and local communities to build the skills and systems that guarantee a healthier future for women and families. Jhpiego translates the best science and practices into moments of care that can mean the difference between life and death for women and families. The moment a woman gives birth; the moment a midwife helps a newborn to breathe. Through our partnerships, we are revolutionizing health care for the world’s most disadvantaged and vulnerable people. In India, Jhpiego works across various states in close collaboration with national and state governments, providing technical assistance in the areas of family planning, maternal and child health, strengthening human resources for health, and non-communicable diseases. These programs are funded by USAID, the Bill &amp; Melinda Gates Foundation, the David &amp; Lucile Packard Foundation, the Children’s Investment Fund Foundation (CIFF), , and other anonymous donors.</p>

<p>The Program Officer, Bioinformatics, operating under the Senior Advisor for Metagenomics &amp; Lab Systems, will play a pivotal role in leveraging bioinformatics to advance the objectives of the Health Security and AMR program. This position offers a unique opportunity to contribute to cutting-edge genomics research and its application in public health.</p>

<p>More detail at https://jobs-jhpiego.icims.com/jobs/5440/program-officer-%e2%80%93-bio-informatics/job</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26919/pear-a-fast-and-accurate-illumina-paired-end-read-merger</guid>
	<pubDate>Wed, 06 Apr 2016 13:27:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26919/pear-a-fast-and-accurate-illumina-paired-end-read-merger</link>
	<title><![CDATA[PEAR: a fast and accurate Illumina Paired-End reAd mergeR]]></title>
	<description><![CDATA[<p><strong>PEAR</strong>&nbsp;is an ultrafast, memory-efficient and highly accurate pair-end read merger. It is fully parallelized and can run with as low as just a few kilobytes of memory.</p>
<p>PEAR evaluates all possible paired-end read overlaps and without requiring the target fragment size as input. In addition, it implements a statistical test for minimizing false-positive results. Together with a highly optimized implementation, it can merge millions of paired end reads within a couple of minutes on a standard desktop computer.</p>
<p>More at&nbsp;http://www.exelixis-lab.org/web/software/pear</p>
<p>Paper:&nbsp;http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3933873/</p><p>Address of the bookmark: <a href="http://www.exelixis-lab.org/web/software/pear" rel="nofollow">http://www.exelixis-lab.org/web/software/pear</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27078/homer-software-for-motif-discovery-and-next-gen-sequencing-analysis</guid>
	<pubDate>Tue, 26 Apr 2016 03:48:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27078/homer-software-for-motif-discovery-and-next-gen-sequencing-analysis</link>
	<title><![CDATA[HOMER:  Software for motif discovery and next-gen sequencing analysis]]></title>
	<description><![CDATA[<p><span>This tutorial covers topics independently of HOMER, and represents knowledge which is important to know before diving head first into more advanced analysis tools such as HOMER.</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/computerSetup.html">Setting up your computing environment</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/retrieveFiles.html">Retrieving and storing sequencing files</a>&nbsp;(your own data or from public sources)</li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/fastqFiles.html">Checking sequence quality, trimming, general sequence manipulation</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/mapping.html">Mapping reads to a reference genome</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/samfiles.html">Manipulating SAM/BAM alignment files</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/genomeBrowsers.html">Visualizing data in a genome browser</a></li>
</ol>
<p><br>RNA-Seq</p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/rnaseqCufflinks.html">De novo transcript discovery and differential analysis with Cufflinks</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/rnaseqR.html">Differential expression analysis with R/Bioconductor</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/clustering.html">Clustering of large expression datasets (microarray or RNA-Seq)</a></li>
</ol>
<p><br><span>Microarray</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/affymetrix.html">Basic analysis of Affymetrix Gene Expression Arrays using R/Bioconductor</a></li>
</ol>
<p><span>General Tips for Data Analysis</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/excelTips.html">Excel workarounds, adding gene annotation, X-Y plots tips, etc.</a></li>
</ol><p>Address of the bookmark: <a href="http://homer.salk.edu/homer/basicTutorial/" rel="nofollow">http://homer.salk.edu/homer/basicTutorial/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27211/srbioinformatics-analyst-ngs-ocimumbio</guid>
  <pubDate>Mon, 02 May 2016 04:41:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Sr.Bioinformatics Analyst (NGS) @ OcimumBio]]></title>
  <description><![CDATA[
<p>Sr.Bioinformatics Analyst (NGS)</p>

<p>Experience Required: 3-5 years of experience<br />No of Positions : Multiple<br />Qualifications: Candidates with minimum qualification as M.Sc Bioinformatics with 3-5  years of experience in Life sciences R&amp;D or Pharma Industry.<br />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.<br />2. Experience in application development or must have expertise in programming using either of Perl/Python.<br />3.  Experience in statistical programming using R/Bioconductor/Matlab.<br />4. Strong concept in statistical and mathematical modelling.<br />5.  Experience in designing and developing the bioinformatics pipeline.<br />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.<br />7. Knowledge in WGS ,WES, Targeted re-sequencing,GWAS and population genomics will be preferred.<br />8. Must have experience working on opensource software/Framework and commercial software for NGS data analysis and reporting.<br />9. Should be aware of handling big data and guiding team members on multiple projects simultaneously.<br />More at http://www.ocimumbio.com/careers1/<br />10. Should have experience coordinating with different groups of clinical research scientist for various project requirements.<br />11. Ability to work as team as well as independently with minimal support.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27216/yass-genomic-similarity-search-tool</guid>
	<pubDate>Mon, 02 May 2016 09:26:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27216/yass-genomic-similarity-search-tool</link>
	<title><![CDATA[YASS :: genomic similarity search tool]]></title>
	<description><![CDATA[<p>YASS is a genomic similarity search tool, for nucleic (DNA/RNA) sequences in fasta or plain text format (<em>it produces local pairwise alignments</em>). Like most of the heuristic pairwise local alignment tools for DNA sequences (FASTA, BLAST, PATTERNHUNTER, BLASTZ/LASTZ, LAST ...), YASS uses <em>seeds</em> to detect potential similarity regions, and then tries to extend them to local alignments. This genomic search tool uses <em>multiple transition constrained spaced seeds</em> that enable to search more fuzzy repeats, as non-coding DNA/RNA. Another simple, but interesting feature is that you can specify the seed pattern used in the search step (as provided for example by <a href="http://bioinfo.lifl.fr/yass/iedera.php">iedera</a>).</p>
<p>Main features of YASS are:</p>
<ul>
<li>multiple, possibly overlapping seeds and a new hit criterion to ensure a good sensitivity/selectivity trade-off</li>
<li>transition-constrained spaced seeds to improve sensitivity (transition mutations are purine to purine [<code>A&lt;-&gt;G</code>] or pyrimidine to pyrimidine [<code>C&lt;-&gt;T</code>])</li>
<li>using different scoring schemes with bit-score and E-value evaluated according to the sequence background frequencies</li>
<li>parameterizable <em>output</em> filter for low complexity repeats</li>
<li>reporting of various alignment statistical parameters (mutation bias along triplets, transition/transversion)</li>
<li>post-processing step to group gapped alignments</li>
</ul><p>Address of the bookmark: <a href="http://bioinfo.lifl.fr/yass/" rel="nofollow">http://bioinfo.lifl.fr/yass/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/27235/supposedly-educational-r</guid>
	<pubDate>Tue, 03 May 2016 16:43:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/27235/supposedly-educational-r</link>
	<title><![CDATA[Supposedly Educational R]]></title>
	<description><![CDATA[<p>R 3.3.0 (codename &ldquo;Supposedly Educational&rdquo;)&nbsp;was <a href="http://r.789695.n4.nabble.com/R-3-3-0-is-released-td4720368.html" target="_blank">released today</a>.&nbsp;You can get the latest binaries version <strong><a href="http://cran.rstudio.com/" target="_blank">from here</a>.</strong>&nbsp;(or the .tar.gz&nbsp;<strong>source</strong> code from <a href="http://cran.r-project.org/src/base/R-3/R-3.3.0.tar.gz" target="_blank">here</a>).&nbsp;The full list of new features and bug fixes is provided below.</p><p>If you are using <strong>Windows&nbsp;</strong>you can easily upgrade to the latest version of R using <a href="http://cran.r-project.org/web/packages/installr/" target="_blank">the installr package</a>. Simply run the following code in Rgui:</p><div><table width="710">
<tbody>
<tr id="p613882">
<td id="p61388code2">
<pre><span style="color: #0000ff; font-weight: bold;">install.<span>packages</span></span><span style="color: #080;">(</span><span style="color: #ff0000;">"installr"</span><span style="color: #080;">)</span> <span style="color: #228b22;"># install </span>
setInternet2<span style="color: #080;">(</span>TRUE<span style="color: #080;">)</span>
installr<span style="color: #080;">::</span><span>updateR</span><span style="color: #080;">(</span><span style="color: #080;">)</span> <span style="color: #228b22;"># updating R.</span></pre>
</td>
</tr>
</tbody>
</table></div><p><span>Running &ldquo;updateR()&rdquo; will detect if there is a new R version available, and if so it will download+install it (etc.). There is also <a href="http://www.r-statistics.com/2015/06/a-step-by-step-screenshots-tutorial-for-upgrading-r-on-windows/" target="_blank">a&nbsp;step by step tutorial (with screenshots) on how to upgrade R on Windows, using the <em>installr</em></a>&nbsp;package. If you only see the option to upgrade to an older version of R, then change your mirror or try again in a few hours (it usually take around 24 hours for all CRAN mirrors to get the latest version of R).</span></p><p><em>I try to keep the <a href="https://github.com/talgalili/installr" target="_blank">installr</a> package updated and useful, so if you have any suggestions or remarks on the package &ndash; you are invited to <a href="https://github.com/talgalili/installr/issues" target="_blank">open an issue in the github page</a>.</em></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/27250/lawley-lab</guid>
  <pubDate>Mon, 09 May 2016 03:29:51 -0500</pubDate>
  <link></link>
  <title><![CDATA[Lawley Lab]]></title>
  <description><![CDATA[
<p>Lawley Lab are covered with a complex microbial community, known as our microbiota, which plays important roles in our physiology, immunity, metabolism and sustenance. Within the human gastrointestinal tract alone there are over 1,000 bacterial species, which amounts to approximately 10 times more cells than we harbor in our entire body and 200 times more genes than are found within our genome. Lawley Lab are really a 'supraorganism' consisting of our 'human' and 'microbial' selves.</p>

<p>More at http://www.sanger.ac.uk/science/groups/lawley-lab</p>
]]></description>
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