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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/17885?offset=90</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28121/kaiju</guid>
	<pubDate>Mon, 27 Jun 2016 11:23:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28121/kaiju</link>
	<title><![CDATA[Kaiju]]></title>
	<description><![CDATA[<p>Kaiju is a program for the taxonomic classification of metagenomic high-throughput sequencing reads. Each read is directly assigned to a taxon within the NCBI taxonomy by comparing it to a reference database containing microbial and viral protein sequences.</p>
<p>By default, Kaiju uses either the available complete genomes from NCBI RefSeq or the microbial subset of the non-redundant protein database <em>nr</em> used by NCBI BLAST, optionally also including fungi and microbial eukaryotes.</p>
<p>Kaiju translates reads into amino acid sequences, which are then searched in the database using a modified backward search on a memory-efficient implementation of the Burrows-Wheeler transform, which finds maximum exact matches (MEMs), optionally allowing mismatches in the protein alignment. The search can process up to millions of reads per minute using, for example, only 10 GB RAM with a protein database comprising 4821 microbial genomes. Kaiju can also be used for querying any other protein database without taxonomic classification, using either protein or nucleotide queries.</p>
<p>Kaiju is described in <a href="http://www.nature.com/ncomms/2016/160413/ncomms11257/full/ncomms11257.html">Menzel, P. et al. (2016) Fast and sensitive taxonomic classification for metagenomics with Kaiju. <em>Nat. Commun.</em> 7:11257</a> (open access).</p><p>Address of the bookmark: <a href="http://kaiju.binf.ku.dk/" rel="nofollow">http://kaiju.binf.ku.dk/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28272/bioinformatics-openings-at-icgeb-new-delhi-india</guid>
  <pubDate>Mon, 04 Jul 2016 01:04:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics openings at ICGEB NEW DELHI, INDIA]]></title>
  <description><![CDATA[
<p>Applications are invited for:</p>

<p>ICGEB NEW DELHI, INDIA</p>

<p>Biotechnology research positions</p>

<p>Projects include:</p>

<p>a) protein structure determination<br />b) malaria parasite biology<br />c) genomics and metagenomics<br />d) molecular and cellular biology<br />e) bioinformatics and computational biology</p>

<p>Minimum eligibility for students who have already obtained a MSc:</p>

<p>1) INSPIRE award for PhD<br />2) SPM award for PhD<br />3) CSIR/DBT/DST JRF for PhD</p>

<p>Applicants should submit their curriculum vitae by email to: sb.icgeb@gmail.com by 30 August 2016</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28415/scarpa</guid>
	<pubDate>Wed, 13 Jul 2016 07:59:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28415/scarpa</link>
	<title><![CDATA[Scarpa]]></title>
	<description><![CDATA[<p><strong>Scarpa</strong>&nbsp;is a stand-alone scaffolding tool for NGS data. It can be used together with virtually any genome assembler and any NGS read mapper that supports SAM format. Other features include support for multiple libraries and an option to estimate insert size distributions from data. Scarpa is available free of charge for academic and commercial use under the GNU General Public License (GPL).</p>
<p>See the&nbsp;<a href="http://compbio.cs.toronto.edu/hapsembler/hapsembler-2.21_manual.pdf">user manual</a>&nbsp;or the&nbsp;<a href="http://compbio.cs.toronto.edu/hapsembler/scarpa_paper.pdf">paper</a>&nbsp;for more information about Scarpa. Click&nbsp;<a href="http://compbio.cs.toronto.edu/hapsembler/ScarpaSupplementary.pdf">here</a>&nbsp;for the supplementary material.</p><p>Address of the bookmark: <a href="http://compbio.cs.toronto.edu/hapsembler/scarpa.html" rel="nofollow">http://compbio.cs.toronto.edu/hapsembler/scarpa.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/28449/aravind-j-shankar-gets-all-india-rank-1-in-binc-2016</guid>
	<pubDate>Tue, 19 Jul 2016 05:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/28449/aravind-j-shankar-gets-all-india-rank-1-in-binc-2016</link>
	<title><![CDATA[Aravind J Shankar gets all India rank 1 in BINC, 2016]]></title>
	<description><![CDATA[<p>Aravind J Shankar, a bioinformatics graduate of SASTRA University, has secured the all India rank 1 in the Bioinformatics National Certification (BINC) 2016, organised by the Department of Biotechnology, Government of India.</p><p>The BINC is a nationwide examination aimed at certifying professionals in bioinformatics and tests their theoretical and practical knowledge across three phases of examination. He is entitled to receive a DBT research fellowship leading to a Ph.D. from any premier research institute in India.</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/28563/find-predicted-crispr-sites-using-ensembl</guid>
	<pubDate>Wed, 27 Jul 2016 03:15:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/28563/find-predicted-crispr-sites-using-ensembl</link>
	<title><![CDATA[Find predicted CRISPR sites using Ensembl]]></title>
	<description><![CDATA[<p>Did you know that you can now use Ensembl to help design your CRISPR experiments? Just turn on the brand new track that shows you the CRISPR sites that have been predicted by the WGE group (<a href="http://www.sanger.ac.uk/science/tools/wge" target="_blank">http://www.sanger.ac.uk/science/tools/wge</a>)</p><p><img src="http://www.ensembl.info/wp-content/uploads/2016/07/Screen-Shot-2016-07-22-at-13.04.33.png" width="1400" height="544" alt="image" style="border: 0px;"></p><p>Find out more on our blog:<br /><a href="http://www.ensembl.info/blog/2016/07/26/find-predicted-crispr-sites-using-ensembl/" target="_blank">http://www.ensembl.info/&hellip;/find-predicted-crispr-sites-usin&hellip;/</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28818/senior-manager-bioinformatics-operations-at-rgcb-india</guid>
  <pubDate>Wed, 17 Aug 2016 03:19:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Manager (Bioinformatics Operations) at RGCB, India]]></title>
  <description><![CDATA[
<p>No. RGCB/ADVT/ADMN&amp;TECH/01/2016</p>

<p>August 17, 2016</p>

<p>RGCB invites applications for the following positions from Indian citizens with prescribed qualifications. Full details including job description, additional desirable qualifications, etc. are described below.</p>

<p>Code No. 1</p>

<p>Senior Manager (Bioinformatics Operations)</p>

<p>(To download application format, click here )</p>

<p>Scale of Pay</p>

<p>PB-3 Rs.15600-39100 + Grade Pay Rs.6600/-</p>

<p>Number of Positions</p>

<p>1 (General)</p>

<p>Minimum Qualifications</p>

<p>PhD in Bioinformatics, Biotechnology, Life Sciences or Computer Science applied to biological questions.<br />A minimum of 5 years documented experience in national or state government R&amp;D centers or state and central universities.<br />Track record of research funding and peer reviewed publications.<br />Proficiency using statistical analysis software or libraries such as R or Matlab.<br />Experience with a general scripting language such as Python, Ruby, or Pearl<br />Experience working with Next Generation Sequencing data<br />Proficiency with data visualization tools (Spotfire, Tableau, R, Python, etc.)<br />Experience with an object-oriented language such as Java, C++ or C# and familiarity with standard software development best practices: source code control, unit testing, in-code documentation and automated build environments.<br />Excellent listening, time management, organizational and interpersonal skills<br />Excellent communication skills, including the ability to illustrate problems and generate solutions<br />Management skills – demonstrated through the successful management of a team or large projects.<br />Broad and deep knowledge of computational methods for high-throughput sequence analysis and interpretation.<br />Extensive experience in delivering bioinformatics as a service and conducting training programs.<br />Experience of working with a production, customer-focused environment and business development projects.<br />Experience with management of funding and financial sustainability.<br />Demonstrated ability to work in a team environment and ability to lead and motivate an effective team, and also work as a good team player.<br />Good problem solver, able to logically identify solutions to technical problems.<br />Able to see the bigger picture and contribute towards strategic direction of Platforms and Pipelines teams.<br />Responsibilities</p>

<p>This position will involve cross-functional teamwork to build and develop bioinformatics tools and provide analysis for ongoing clinical trials.<br />Collaborate with biomarker scientists, clinical investigators and pipeline teams to build analytical tools.<br />Implement and evaluate new algorithms for R&amp;D.<br />Support Research and Development teams by analyzing NGS data to identify predictive response markers<br />Lead training programs in Computational Biology and Bioinformatics.</p>

<p>More at http://rgcb.res.in/positions.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29103/genome-strip</guid>
	<pubDate>Tue, 06 Sep 2016 03:58:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29103/genome-strip</link>
	<title><![CDATA[Genome STRiP]]></title>
	<description><![CDATA[<p><strong>Genome STRiP</strong><span>&nbsp;(Genome STRucture In Populations) is a suite of tools for discovering and genotyping structural variations using sequencing data. The methods are designed to detect shared variation using data from multiple individuals.</span><br><br><span>Genome STRiP looks both across and within a set of sequenced genomes to detect variation. The methods are adaptive and support heterogeneous data sets, including variations in sequencing depth, read lengths and mixtures of paired and single-end reads. A minimum of 20 to 30 genomes are required to get acceptable results, but the method gains power across genomes and processing more genomes provide better results.</span><br><br><span>To run discovery or genotyping on a single sequenced genome or a small set of genomes, you need to call your data against a background population, such as a set of genomes from the 1000 Genomes Project.&nbsp; The background population does not need to be matched to the target individuals.</span></p><p>Address of the bookmark: <a href="http://software.broadinstitute.org/software/genomestrip/" rel="nofollow">http://software.broadinstitute.org/software/genomestrip/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29018/crossmap</guid>
	<pubDate>Mon, 05 Sep 2016 04:07:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29018/crossmap</link>
	<title><![CDATA[CrossMap]]></title>
	<description><![CDATA[<ul>
<li>CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between&nbsp;<em>different assemblies</em>&nbsp;(such as Human&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/2928/">hg18 (NCBI36)</a>&nbsp;&lt;&gt;&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/2758/">hg19 (GRCh37)</a>, Mouse&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/165668/">mm9 (MGSCv37)</a>&nbsp;&lt;&gt;&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/327618/">mm10 (GRCm38)</a>).</li>
<li>It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.</li>
<li>CrossMap is designed to liftover genome coordinates between assemblies. It&rsquo;s&nbsp;<em>not</em>&nbsp;a program for aligning sequences to reference genome.</li>
<li>We&nbsp;<em>do not</em>&nbsp;recommend using CrossMap to convert genome coordinates between species.</li>
</ul><p>Address of the bookmark: <a href="http://crossmap.sourceforge.net/" rel="nofollow">http://crossmap.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28807/organellargenomedraw</guid>
	<pubDate>Tue, 16 Aug 2016 08:13:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28807/organellargenomedraw</link>
	<title><![CDATA[OrganellarGenomeDRAW]]></title>
	<description><![CDATA[<p><span>O</span><span>rganellar</span><span>G</span><span>enome</span><span>DRAW</span><span>&nbsp;is dedicated to convert genetic information stored in GenBank entries to graphical maps. The input text file has to be in GenBank flat file format, whereas the output format can be chosen among several formats. The application is especially optimized and adapted for the creation of high-quality, detailed circular maps of organellar genomes like the plastid genome (plastome) or the mitochondrial genome (chondriome). Nevertheless, you can upload any GenBank entry. The workflow is devided into three steps.&nbsp;</span></p>
<p><span>More at&nbsp;http://ogdraw.mpimp-golm.mpg.de/cgi-bin/ogdraw.pl</span></p><p>Address of the bookmark: <a href="http://ogdraw.mpimp-golm.mpg.de/index.shtml" rel="nofollow">http://ogdraw.mpimp-golm.mpg.de/index.shtml</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28844/teannot</guid>
	<pubDate>Thu, 18 Aug 2016 10:02:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28844/teannot</link>
	<title><![CDATA[TEannot]]></title>
	<description><![CDATA[<p>We advise to run first the TEdenovo pipeline but it is not compulsory. We suppose you begin by running the TEannot pipeline on the example provided in the directory "db/" rather than directly on your own genomic sequences. Thus, from now on, the project name is "DmelChr4".</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto" rel="nofollow">https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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