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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/35257?offset=350</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25674/post-doc-position-at-labgem-evry-france</guid>
  <pubDate>Fri, 11 Dec 2015 06:24:00 -0600</pubDate>
  <link></link>
  <title><![CDATA[Post-doc position at LABGeM - Evry, France]]></title>
  <description><![CDATA[
<p>The LABGeM team (CEA/Genoscope, CNRS UMR 8030, France, Dir. Claudine Médigue) is developing integrated approaches which combines bioinformatics methods based (i) on genomic and metabolic contexts, (ii) on an orignal metabolic network representation and (iii) on a structural classification of active sites for the discovery of new metabolic enzymatic activities.</p>

<p>We are hiring a post-doctoral fellow for the development of innovative bioinformatics methods to explore metabolic networks and enzyme families. These methods will be based on protein family analysis and graph approaches combining genomic and metabolic contexts.</p>

<p>For more details, please see this link : http://goo.gl/tHQOqk</p>

<p>Qualifications:<br />PhD degree in bioinformatics or computational biology<br />- Previous experience in network or protein family analysis<br />- Programming skills (C/C++, Python, Java) and in common biostatistical analyses<br />- Team player, innovative and creative thinking, good oral and written communication skills</p>

<p>24 months, Post Doctoral position<br />Start: from March 2016<br />Place: CEA, Genoscope UMR8030, LABGeM (Laboratory of Bioinformatics Analyses for Genomics and Metabolism), Evry, France<br />Contact: David Vallenet, vallenet@genoscope.cns.fr<br />Publications: https://scholar.google.com/citations?user=rJNPLSAAAAAJ<br />Remuneration per month: from 2,850 €</p>

<p>Interested candidates should send their CV, statement of research interests, and contact information of at least 2 references to David Vallenet (vallenet@genoscope.cns.fr).</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26559/microscope</guid>
	<pubDate>Fri, 04 Mar 2016 05:26:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26559/microscope</link>
	<title><![CDATA[Microscope]]></title>
	<description><![CDATA[<p>Microscope Platform user documentation.</p>
<p>The MicroScope platform is available at this URL:</p>
<p><a href="https://www.genoscope.cns.fr/agc/microscope">https://www.genoscope.cns.fr/agc/microscope</a></p><p>Address of the bookmark: <a href="http://microscope.readthedocs.org/en/latest/index.html" rel="nofollow">http://microscope.readthedocs.org/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26332/pilon</guid>
	<pubDate>Mon, 08 Feb 2016 15:56:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26332/pilon</link>
	<title><![CDATA[Pilon]]></title>
	<description><![CDATA[<p>Pilon is a software tool which can be used to:</p>
<ul>
<li>Automatically improve draft assemblies</li>
<li>Find variation among strains, including large event detection</li>
</ul>
<p>Pilon requires as input a FASTA file of the genome along with one or more BAM files of reads aligned to the input FASTA file. Pilon uses read alignment analysis to identify inconsistencies between the input genome and the evidence in the reads. It then attempts to make improvements to the input genome, including:</p>
<ul>
<li>Single base differences</li>
<li>Small indels</li>
<li>Larger indel or block substitution events</li>
<li>Gap filling</li>
<li>Identification of local misassemblies, including optional opening of new gaps</li>
</ul>
<p>More at https://github.com/broadinstitute/pilon/wiki</p><p>Address of the bookmark: <a href="https://github.com/broadinstitute/pilon/wiki" rel="nofollow">https://github.com/broadinstitute/pilon/wiki</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26363/flo</guid>
	<pubDate>Wed, 10 Feb 2016 10:52:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26363/flo</link>
	<title><![CDATA[flo]]></title>
	<description><![CDATA[<p>flo - same species annotations lift over pipeline</p>
<p>Lift over is the process of transferring annotations from one genome assembly to another. Usually lift over is done because there is a new, improved genome assembly for the species and good quality annotations (maybe manually curated or experimentally verified) are available on the old assembly.</p>
<p>The idea is simple: align the new assembly with the old one (e.g., with BLAT), process the alignment data to define how a coordinate or coordinate range on the old assembly should be transformed to the new assembly (e.g., as a chain file), transform the coordinates (e.g., with liftOver).</p>
<p>&nbsp;</p>
<p>https://github.com/wurmlab/flo</p><p>Address of the bookmark: <a href="https://github.com/wurmlab/flo" rel="nofollow">https://github.com/wurmlab/flo</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26535/svelter</guid>
	<pubDate>Mon, 29 Feb 2016 17:33:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26535/svelter</link>
	<title><![CDATA[svelter]]></title>
	<description><![CDATA[<p>This software is designed to identify both simple and complex rearrangements from paired-end sequencing data. Users could ran it easily by just alling&nbsp;<em>SVelter.py</em>&nbsp;with proper parameters. It's also possible to ran it on multiple cores by calling different sub-functions separately.</p>
<p>More at&nbsp;https://github.com/mills-lab/svelter/</p><p>Address of the bookmark: <a href="https://github.com/mills-lab/svelter/" rel="nofollow">https://github.com/mills-lab/svelter/</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27113/picard</guid>
	<pubDate>Fri, 29 Apr 2016 08:21:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27113/picard</link>
	<title><![CDATA[Picard]]></title>
	<description><![CDATA[<p>Picard is a set of command line tools for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF. These file formats are defined in the <a href="http://samtools.github.io/hts-specs/">Hts-specs</a> repository. See especially the <a href="http://samtools.github.io/hts-specs/SAMv1.pdf">SAM specification</a> and the <a href="http://samtools.github.io/hts-specs/VCFv4.3.pdf">VCF specification</a>.</p>
<p>Note that the information on this page is targeted at end-users. For developers, the source code, building instructions and implementation/development resources are available on <a href="https://github.com/broadinstitute/picard">GitHub</a>.</p>
<p>The Picard toolkit is open-source under the <a href="https://tldrlegal.com/license/mit-license">MIT license</a> and free for all uses.</p>
<p>Enjoy!</p><p>Address of the bookmark: <a href="http://broadinstitute.github.io/picard/" rel="nofollow">http://broadinstitute.github.io/picard/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26909/sequence-assembly-with-mira-4</guid>
	<pubDate>Wed, 06 Apr 2016 08:21:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26909/sequence-assembly-with-mira-4</link>
	<title><![CDATA[Sequence assembly with MIRA 4]]></title>
	<description><![CDATA[<p>MIRA is a multi-pass DNA sequence data assembler/mapper for whole genome and EST/RNASeq projects. MIRA assembles/maps reads gained by</p>
<div>
<ul>
<li>
<p>electrophoresis sequencing (aka Sanger sequencing)</p>
</li>
<li>
<p>454 pyro-sequencing (GS20, FLX or Titanium)</p>
</li>
<li>
<p>Ion Torrent</p>
</li>
<li>
<p>Solexa (Illumina) sequencing</p>
</li>
<li>
<p>(in development) Pacific Biosciences sequencing</p>
</li>
</ul>
</div>
<p>into contiguous sequences (called <span><em>contigs</em></span>). One can use the sequences of different sequencing technologies either in a single assembly run (a <span><em>true hybrid assembly</em></span>) or by mapping one type of data to an assembly of other sequencing type (a <span><em>semi-hybrid assembly (or mapping)</em></span>) or by mapping a data against consensus sequences of other assemblies (a <span><em>simple mapping</em></span>).</p>
<p>The MIRA acronym stands for <span><strong>M</strong></span>imicking <span><strong>I</strong></span>ntelligent <span><strong>R</strong></span>ead <span><strong>A</strong></span>ssembly and the program pretty well does what its acronym says (well, most of the time anyway). It is the Swiss army knife of sequence assembly that I've used and developed during the past 14 years to get assembly jobs I work on done efficiently - and especially accurately. That is, without me actually putting too much manual work into it.</p>
<p>More at http://mira-assembler.sourceforge.net/docs/DefinitiveGuideToMIRA.html</p><p>Address of the bookmark: <a href="http://mira-assembler.sourceforge.net/docs/DefinitiveGuideToMIRA.html" rel="nofollow">http://mira-assembler.sourceforge.net/docs/DefinitiveGuideToMIRA.html</a></p>]]></description>
	<dc:creator>Priya Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26923/quast-quality-assessment-tool-for-genome-assemblies</guid>
	<pubDate>Wed, 06 Apr 2016 18:23:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26923/quast-quality-assessment-tool-for-genome-assemblies</link>
	<title><![CDATA[QUAST: quality assessment tool for genome assemblies]]></title>
	<description><![CDATA[<p><span>QUAST evaluates genome assemblies. For metagenomes, please see&nbsp;<a href="http://bioinf.spbau.ru/metaquast">MetaQUAST</a>&nbsp;project.</span><br><span>It can works both with and without a given reference genome.</span><br><span>The tool accepts multiple assemblies, thus is suitable for comparison.</span></p>
<p><span>More at&nbsp;http://bioinf.spbau.ru/quast</span></p>
<p><span>http://bioinformatics.oxfordjournals.org/content/early/2013/03/09/bioinformatics.btt086.long</span></p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2013/03/09/bioinformatics.btt086.long" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2013/03/09/bioinformatics.btt086.long</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26972/understanding-fastqc-output</guid>
	<pubDate>Fri, 15 Apr 2016 05:47:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26972/understanding-fastqc-output</link>
	<title><![CDATA[Understanding Fastqc Output]]></title>
	<description><![CDATA[<p>Understanding Following table and graphs</p>
<ol>
<li>Duplication level</li>
<li>kmer profile</li>
<li>per base GC content</li>
<li>per base N content</li>
<li>per base quality</li>
<li>per base sequence content</li>
<li>per sequence GC content</li>
<li>per sequence quality</li>
<li>sequence length distribution</li>
</ol>
<p>More at http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/</p><p>Address of the bookmark: <a href="http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/" rel="nofollow">http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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