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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26380?offset=1030</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27328/platanus</guid>
	<pubDate>Fri, 13 May 2016 05:12:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27328/platanus</link>
	<title><![CDATA[Platanus]]></title>
	<description><![CDATA[<p>Platanus is a novel <em>de novo</em> sequence assembler that can reconstruct genomic sequences of<br> highly heterozygous diploids from massively parallel shotgun sequencing data.</p>
<p>The latest version is <a href="http://platanus.bio.titech.ac.jp/platanus/?page_id=14">1.2.4</a>.</p>
<p>To cite Platanus, please use the following:</p>
<p>Kajitani R, Toshimoto K, Noguchi H, Toyoda A, Ogura Y, Okuno M, Yabana M, Harada M, Nagayasu E, Maruyama H, Kohara Y, Fujiyama A, Hayashi T, Itoh T, &ldquo;Efficient de novo assembly of highly heterozygous genomes from whole-genome shotgun short reads&rdquo;.&nbsp;Genome Res. 2014 Aug;24(8):1384-95. doi: 10.1101/gr.170720.113. [<a href="http://www.ncbi.nlm.nih.gov/pubmed/24755901">abstract</a> |<a href="http://genome.cshlp.org/content/24/8/1384.long"> full text</a>]</p><p>Address of the bookmark: <a href="http://platanus.bio.titech.ac.jp/" rel="nofollow">http://platanus.bio.titech.ac.jp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/27412/navin-lab</guid>
  <pubDate>Wed, 18 May 2016 16:40:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[Navin Lab]]></title>
  <description><![CDATA[
<p>NAvin laboratory has pioneered the development of single cell sequencing technologies.  They apply these tools to study complex biological processes that occur in human cancers including tumor initation, clonal evolution, invasion, metastasis and chemoresistance.  These processes have previously been difficult to study with genomic technologies using bulk tissues</p>

<p>More at http://www.navinlab.com/navinlab/home.html</p>
]]></description>
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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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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27453/senior-project-fellow-bioinformatics-at-nbri</guid>
  <pubDate>Sat, 21 May 2016 21:01:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Project Fellow Bioinformatics at NBRI]]></title>
  <description><![CDATA[
<p>Walk In Interview No. 03/Project/2016<br />Senior Project Fellow Bioinformatics Job vacancies in CSIR- National Botanical Research Institute (NBRI), Lucknow<br />Area III: Molecular Biology &amp; Biotechnology<br />Qualification : 1st Class M.Sc. in Bioinformatics/Biotechnology/ Life Science /Biochemistry/Botany with 2 years research experience and at least one publication in SCI Journal or 1st class M.Tech in Bioinformatics<br />Age : 32 years<br />Salary : Rs.18000<br />How to apply<br />Date &amp; Venue of Interview For Area III: 27-05-2016 at 11.00 A.M. at Conference Room, T.N. Khushoo Block, NBRI, Lucknow.</p>

<p>http://www.nbri.res.in/temp.php</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27465/stand-alone-programs-for-bioinformatician</guid>
	<pubDate>Sat, 21 May 2016 22:50:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27465/stand-alone-programs-for-bioinformatician</link>
	<title><![CDATA[Stand-alone programs for Bioinformatician]]></title>
	<description><![CDATA[<p>This directory contains applications for stand-alone use, built specifically for a Linux 64-bit machine.</p>
<p>For help on the bigBed and bigWig applications see:<br>http://genome.ucsc.edu/goldenPath/help/bigBed.html<br>http://genome.ucsc.edu/goldenPath/help/bigWig.html</p>
<p>View the file 'FOOTER' to see the usage statement for each of the applications.</p><p>Address of the bookmark: <a href="http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/" rel="nofollow">http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27540/research-associate-bioinformatics-at-manit</guid>
  <pubDate>Thu, 26 May 2016 02:20:58 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate Bioinformatics at MANIT]]></title>
  <description><![CDATA[
<p>Research Associate Jobs opportunity in Maulana Azad National Institute of Technology (MANIT) on contract basis<br />Project : “Screening of Anti-venom potential of medicinal plants from Tribal region of Madhya Pradesh"<br />No. of Post : 01</p>

<p>Qualification : The minimum qualifications are : Ph.D in Bioinformatics/ Biotechnology or allied branches with atleast two publication in SCI journals.<br />Fellowship : The consolidated emoluments of Rs.36, 000/ PM+HRA+MA as per CSIR rules.</p>

<p>How to apply<br />Applications (in prescribed attached format and supporting documents) to be received in the Dr. Rahul Shrivastava, Principal Investigator (CSIR Project), Department of Biological Science and Engineering, Maulana Azad National Institute of Technology, Bhopal – 462003 (MP) on or before 7th June 2016.</p>

<p>More at http://www.web.manit.ac.in/Year%202016/Recruitment%20Contract%20Faculty/Biological/Advertisement%20for%20Antivenome%20project%202.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27685/biodbnet</guid>
	<pubDate>Thu, 02 Jun 2016 11:11:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27685/biodbnet</link>
	<title><![CDATA[BioDBnet]]></title>
	<description><![CDATA[<p><span>Database to Database Conversions</span> </p>
<p>db2db allows for conversions of identifiers from one database to other database identifiers or annotations. To use db2db select the input type of your data, changing the input type automatically changes the output options to the ones specific for the input selected. Then select one or more output types and add your identifiers in the ID list box. Set the remove duplicate values to 'No' if you do not want duplicates to be removed. Clicking on submit then returns a table of your inputs matched against all the outputs selected in the exact order as entered. Results can be limited to a particular taxon by entering it's <a href="https://biodbnet-abcc.ncifcrf.gov/tools/orgTaxon.php">Taxon ID</a>. The performance will vary widely depending on the number of outputs and the options selected. Conversions to a single output with the default options should complete in a few seconds</p><p>Address of the bookmark: <a href="https://biodbnet-abcc.ncifcrf.gov/db/db2db.php" rel="nofollow">https://biodbnet-abcc.ncifcrf.gov/db/db2db.php</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/27713/mutabind</guid>
	<pubDate>Mon, 06 Jun 2016 13:34:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/27713/mutabind</link>
	<title><![CDATA[MutaBind]]></title>
	<description><![CDATA[<p><span>MutaBind is a new computational method and server created through NCBI research efforts that maps mutations on a protein structural complex, calculates changes in binding affinity, identifies deleterious mutations and produces a downloadable mutant structural model.&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/projects/mutabind/index.fcgi/" target="_blank">http://www.ncbi.nlm.nih.gov/projects/mutabind/index.fcgi/</a></p><p><img src="http://www.ncbi.nlm.nih.gov/projects/mutabind/prj-sunddg/static/myimgs/CirclesDiamondBlueThiner.png" width="471" height="258" alt="image" style="border: 0px;"></p><p><span>MutaBind guides you through this process, step by step, starting with selecting a protein complex and inputting PDB code or uploading PDB files. You can also retrieve results with a job ID number, view help documents, and review the MutaBind method and references.</span></p><p><span>More at&nbsp;http://www.ncbi.nlm.nih.gov/projects/mutabind/index.fcgi/</span></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27818/gaemr</guid>
	<pubDate>Tue, 14 Jun 2016 06:18:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27818/gaemr</link>
	<title><![CDATA[GAEMR]]></title>
	<description><![CDATA[<p>The&nbsp;<span>G</span>enome&nbsp;<span>A</span>ssembly&nbsp;<span>E</span>valuation&nbsp;<span>M</span>etrics and&nbsp;<span>R</span>eporting (GAEMR) package is an assembly analysis framework composed a number of integrated modules. These modules can be executed as a single program to generate a complete analysis report, or executed individually to generate specific charts and tables. GAEMR standardizes input by converting a variety of read types to Binary Alignment Map (BAM) format, allowing a single input format to be entered into GAEMR&rsquo;s analysis pipeline, hence enabling the generation of standard reports.</p>
<p>GAEMR&rsquo;s analysis philosophy is centered on contiguity, correctness, and completeness -- how many pieces in an assembly composed of, how well those pieces accurately represent the genome sequenced, and how much of that genome is represented by those pieces. By performing over twenty different analyses based on these principles, GAEMR gives a clear picture of the condition of a genome assembly.&nbsp;</p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/software/gaemr/" rel="nofollow">https://www.broadinstitute.org/software/gaemr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27841/covcal-coverage-read-count-calculator</guid>
	<pubDate>Wed, 15 Jun 2016 18:08:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27841/covcal-coverage-read-count-calculator</link>
	<title><![CDATA[CovCal: Coverage / Read Count Calculator]]></title>
	<description><![CDATA[<h2>Coverage / Read Count Calculator</h2>
<h4>Calculate how much sequencing you need to hit a target depth of coverage (or vice versa).</h4>
<p><span>Instructions:</span> set the read length/configuration and genome size, then select what you want to calculate.</p>
<p>Written by <a href="http://stephenturner.us/" target="blank">Stephen Turner</a>, based on the <a href="http://www.ncbi.nlm.nih.gov/pubmed/3294162" target="_blank">Lander-Waterman formula</a>, inspired by <a href="http://core-genomics.blogspot.com/2016/05/how-many-reads-to-sequence-genome.html" target="_blank">a similar calculator</a> written by James Hadfield. Coverage is calculated as <em>C=LN/G</em> and reads as <em>N=CG/L</em> where <em>C</em> = Coverage (X),<em>L</em> = Read length (bp), <em>G</em> = Haploid genome size (bp), and <em>N</em> = Number of reads. Source code <a href="https://github.com/stephenturner/covcalc" target="_blank">on GitHub</a>.</p><p>Address of the bookmark: <a href="http://apps.bioconnector.virginia.edu/covcalc/" rel="nofollow">http://apps.bioconnector.virginia.edu/covcalc/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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