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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31089?offset=560</link>
	<atom:link href="https://bioinformaticsonline.com/related/31089?offset=560" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26968/scalce</guid>
	<pubDate>Fri, 15 Apr 2016 05:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26968/scalce</link>
	<title><![CDATA[SCALCE]]></title>
	<description><![CDATA[<p><span>SCALCE (</span><code>/skeɪlz/</code><span>, a.k.a. boosting&nbsp;</span><span style="text-decoration: underline;">S</span><span>equence&nbsp;</span><span style="text-decoration: underline;">C</span><span>ompression&nbsp;</span><span style="text-decoration: underline;">A</span><span>lgorithms using&nbsp;</span><span style="text-decoration: underline;">L</span><span>ocally&nbsp;</span><span style="text-decoration: underline;">C</span><span>onsistent</span><span style="text-decoration: underline;">E</span><span>ncoding) is a tool for compressing FASTQ files. It is designed specifically for the Illumina-generated FASTQ files, but supports any valid FASTQ with consistent read lengths.&nbsp;</span></p>
<p><span>More at&nbsp;http://sfu-compbio.github.io/scalce/</span></p><p>Address of the bookmark: <a href="http://sfu-compbio.github.io/scalce/" rel="nofollow">http://sfu-compbio.github.io/scalce/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/31523/research-associate-bioinformatics-recruitment-in-national-bureau-of-plant-genetic-resources</guid>
  <pubDate>Fri, 10 Mar 2017 06:50:51 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Associate Bioinformatics recruitment in National Bureau of Plant Genetic Resources]]></title>
  <description><![CDATA[
<p>Name of Project  : Indo-UK Centre for improvement of Nitrogen use efficiency in wheat Dr. Soma S. Marla, Pr. Scientist (Bioinformatics), Division of Genomic Resources, ICAR, NBPGR, ND. </p>

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

<p>Qualification : A doctoral (Ph.D). Degree in Bioinformatics OR 1. Masters degree in Bioinformatics or Computer Sciences having 1st division or 60% marks or equivalent overall grade point with at least two years of research experience as evidenced from Fellowship/ Associate ship. 2. NET or equivalent national level examination qualification is essential for the candidates with 3+2 years (B.Sc.+ M.Sc) pattern. Desirable: Demonstrated experience &amp; skills in database design, management, UNIX OS, HPC environment inbased NGS data analysis. Experience substantiated by publications of high quality will be preferred.</p>

<p>Emoluments : Rs. 40,000 (Ph.D)/ Rs + 30 % HRA; 38,000 (Masters) Degree + 30 % HRA.<br />Hiring Process : Walk - In<br />Job Role: Research/JRF/SRF</p>

<p>Candidates should appear by 10.00 AM on 16.03.2016 for registration with relevant documents in the room B4, Bioinformatics Lab, ICAR.NBPGR. old campus, Inderpuri, New Delhi.</p>

<p>The candidates who wish to attend the walk-in interview are requested to bring with them five copies of the CV (one copy with photograph) as per the format given below. Also, the candidates should bring the original documents such as DOB, degree certificates, marks sheets, publications, thesis, experience certificate etc. for verification.</p>

<p>http://www.nbpgr.ernet.in/Downloadfile.aspx?EntryId=7284</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27092/medea-comparative-genomic-visualization-with-adobe-flash</guid>
	<pubDate>Tue, 26 Apr 2016 12:15:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27092/medea-comparative-genomic-visualization-with-adobe-flash</link>
	<title><![CDATA[MEDEA: Comparative Genomic Visualization with Adobe Flash]]></title>
	<description><![CDATA[<p><span>As the number of sequence and annotated genomes grows larger, the need to understand, compare, and contrast the data becomes increasingly important. Using the power of the human visual system to detect trends and spot outliers is necessary in such large and complex data sets.</span></p>
<p><span>More at&nbsp;http://www.broadinstitute.org/annotation/medea/</span></p><p>Address of the bookmark: <a href="http://www.broadinstitute.org/annotation/medea/" rel="nofollow">http://www.broadinstitute.org/annotation/medea/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27099/rasttk-algorithm-for-building-custom-annotation-pipelines-and-annotating-batches-of-genomes</guid>
	<pubDate>Wed, 27 Apr 2016 11:07:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27099/rasttk-algorithm-for-building-custom-annotation-pipelines-and-annotating-batches-of-genomes</link>
	<title><![CDATA[RASTtk : algorithm for building custom annotation pipelines and annotating batches of genomes]]></title>
	<description><![CDATA[<p>The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.</p>
<p>More at http://www.nature.com/articles/srep08365</p><p>Address of the bookmark: <a href="http://rast.nmpdr.org/" rel="nofollow">http://rast.nmpdr.org/</a></p>]]></description>
	<dc:creator>Abhi</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>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27240/bioinformatics-tutor-at-pgimer</guid>
  <pubDate>Wed, 04 May 2016 08:40:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Tutor at PGIMER]]></title>
  <description><![CDATA[
<p>Postgraduate Institute of Medical Education and Research (PGIMER) - Chandigarh, Chandigarh<br />₹9,300 - ₹34,800 a month<br />Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh invites Online Applications for recruitment of following Group 'A', 'B' and 'C' posts. The closing date for submission of online applications is up to 12th May 2016.</p>

<p>No of Vacancies: 01<br />Pay Scale: Rs. 9300-34800 + Grade Pay Rs. 4600/-</p>

<p>Educational Qualification and Experience: (From Recognized University / Institute) M.Sc. in Biotechnology, Molecular Biology, Human Genomics / Biochemistry / Biophysics.</p>

<p>Age Limit: 18-50 years</p>

<p>Please see Detailed Advertisement Link for full info: https://drive.google.com/file/d/0Bz3xO6e_7OeeZllINnRyWlN5UFE/view</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27291/summer-internship-positions-at-dupont</guid>
  <pubDate>Wed, 11 May 2016 08:05:54 -0500</pubDate>
  <link></link>
  <title><![CDATA[Summer internship positions at DuPont]]></title>
  <description><![CDATA[
<p>DuPont Industrial Biosciences has several summer internship positions<br />for undergrads available. We are looking for driven and creative interns<br />to conduct research in the following areas:</p>

<p>· Enzyme immobilization supports for select enzyme systems.</p>

<p>· New tools for microbial strain and genome engineering using<br />state-of-the-art methodologies.</p>

<p>· Rapid high throughput assays to screen microorganisms from various<br />sources for enzymatic activities of interest.</p>

<p>· High throughput combinatorial approaches to the formulation of growth<br />media in support of microbial enrichments, strain isolations and growth<br />optimization.</p>

<p>· Meta-transcriptomics for the discovery of new enzymes.</p>

<p>· Strain adaptation techniques in defined chemostat environments for<br />microbial strain development.</p>

<p>The internships are based at the Experimental Station R&amp;D Center in<br />Wilmington, DE.</p>

<p>If interested, apply fast!</p>

<p>For more information and to apply, go to:</p>

<p>http://careers.dupont.com/jobsearch/job-details/industrial-biosciences-summer-internship/008549W-10/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/27321/slurm-basics</guid>
	<pubDate>Fri, 13 May 2016 04:42:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/27321/slurm-basics</link>
	<title><![CDATA[SLURM basics !]]></title>
	<description><![CDATA[<p><a href="http://bioinformaticsonline.com/bookmarks/view/27238/slurm" target="_blank">SLURM</a> is a queue management system and stands for Simple Linux Utility for Resource Management. SLURM was developed at the Lawrence Livermore National Lab and currently runs some of the largest compute clusters in the world.</p><p>SLURM is similar in many ways to most other queue systems. You write a batch script then submit it to the queue manager. The queue manager then schedules your job to run on the queue (or partition in SLURM parlance) that you designate. Below we will provide an outline of how to submit jobs to SLURM, how SLURM decides when to schedule your job and how to monitor progress.</p><p>SLURM has a number of valuable features compared to other job management systems:</p><ul>
<li><em>Kill and Requeue</em> SLURM&rsquo;s ability to kill and requeue is superior to that of other systems. It waits for jobs to be cleared before scheduling the high priority job. It also does kill and requeue on memory rather than just on core count.</li>
<li><em>Memory</em> Memory requests are sacrosanct in SLURM. Thus the amount of memory you request at run time is guaranteed to be there. No one can infringe on that memory space and you cannot exceed the amount of memory that you request.</li>
<li><em>Accounting Tools</em> SLURM has a back end database which stores historical information about the cluster. This information can be queried by the users who are curious about how much resources they have used.</li>
</ul><p><strong>Summary of SLURM commands</strong></p><p>The table below shows a summary of SLURM commands. These commands are described in more detail below along with links to the SLURM doc site.</p><table>
<tbody>
<tr><th>&nbsp;</th><th>SLURM</th><th>SLURM Example</th></tr>
<tr>
<td>Submit a batch serial job</td>
<td><a href="http://slurm.schedmd.com/sbatch.html">sbatch</a></td>
<td><code>sbatch runscript.sh</code></td>
</tr>
<tr>
<td>Run a script interatively</td>
<td><a href="http://slurm.schedmd.com/srun.html">srun</a></td>
<td><code>srun --pty -p interact -t 10 --mem 1000 /bin/bash /bin/hostname</code></td>
</tr>
<tr>
<td>Kill a job</td>
<td><a href="http://slurm.schedmd.com/scancel.html">scancel</a></td>
<td><code>scancel 999999</code></td>
</tr>
<tr>
<td>View status of queues</td>
<td><a href="http://slurm.schedmd.com/squeue.html">squeue</a></td>
<td><code>squeue -u akitzmiller</code></td>
</tr>
<tr>
<td>Check current job by id</td>
<td><a href="http://slurm.schedmd.com/squeue.html">sacct</a></td>
<td><code>sacct -j 999999</code></td>
</tr>
</tbody>
</table>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/27344/orffinder-with-smart-blast</guid>
	<pubDate>Tue, 17 May 2016 01:43:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/27344/orffinder-with-smart-blast</link>
	<title><![CDATA[ORFfinder with smart BLAST]]></title>
	<description><![CDATA[<p><span>ORF Finder</span></p><p><span><a href="http://www.ncbi.nlm.nih.gov/orffinder">ORFfinder</a><span>&nbsp;is a graphical analysis tool for finding open reading frames (ORFs). We&rsquo;ve been working on a few updates, and we&rsquo;d like to find out what you think about them. Read on to find out what you can do with the new ORFfinder.</span></span></p><p>Smart BLAST (https://ncbiinsights.ncbi.nlm.nih.gov/2015/07/29/smartblast/)</p><p>Select one or a group of ORFs and BLAST several databases at once, and use the newly developed&nbsp;<a href="http://blast.ncbi.nlm.nih.gov/smartblast/">SmartBLAST</a>&nbsp;to verify protein names.&nbsp;Looking for the traditional results from&nbsp;<a href="http://blast.ncbi.nlm.nih.gov/Blast.cgi">BLAST</a>? They&rsquo;re there too.</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27430/mosaik-a-hash-based-algorithm-for-accurate-next-generation-sequencing-short-read-mapping</guid>
	<pubDate>Fri, 20 May 2016 18:53:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27430/mosaik-a-hash-based-algorithm-for-accurate-next-generation-sequencing-short-read-mapping</link>
	<title><![CDATA[MOSAIK: A Hash-Based Algorithm for Accurate Next-Generation Sequencing Short-Read Mapping]]></title>
	<description><![CDATA[<p><span>MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery.</span></p><p>Address of the bookmark: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0090581" rel="nofollow">http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0090581</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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