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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31564?offset=920</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13014/bioinformatics-jrf-vacancy-at-icgeb-new-delhi</guid>
  <pubDate>Wed, 23 Jul 2014 16:07:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF vacancy at ICGEB, New Delhi]]></title>
  <description><![CDATA[
<p>Junior Research Fellow for a DBT sponsored project entitled "Computational and experimental characterization of stage specific arginine methylation in P. falciparum proteome". </p>

<p>Candidates should have a 1st class MSc/MTech/BTech degree in Bioinformatics. Please send complete CV, quoting Application for RMETH-JRF-2014, by email to Dr. Dinesh Gupta: dinesh@icgeb.res.in</p>

<p>Closing date for applications: 6 August 2014</p>

<p>More at http://www.icgeb.org/tl_files/Vacancies/JRF.pdf</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35571/medusa-a-multi-draft-based-scaffolder</guid>
	<pubDate>Wed, 14 Feb 2018 02:49:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35571/medusa-a-multi-draft-based-scaffolder</link>
	<title><![CDATA[MeDuSa: a multi-draft based scaffolder]]></title>
	<description><![CDATA[<p><span>MeDuSa (Multi-Draft based Scaffolder), an algorithm for genome scaffolding. MeDuSa exploits information obtained from a set of (draft or closed) genomes from related organisms to determine the correct order and orientation of the contigs. MeDuSa formalises the scaffolding problem by means of a combinatorial optimisation formulation on graphs and implements an efficient constant factor approximation algorithm to solve it. In contrast to currently used scaffolders, it does not require either prior knowledge on the microrganisms dataset under analysis (e.g. their phylogenetic relationships) or the availability of paired end read libraries.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/combogenomics/medusa" rel="nofollow">https://github.com/combogenomics/medusa</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11313/linux-sort-commands-for-bioinformatics</guid>
	<pubDate>Sat, 31 May 2014 15:41:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11313/linux-sort-commands-for-bioinformatics</link>
	<title><![CDATA[Linux Sort Commands for Bioinformatics]]></title>
	<description><![CDATA[<p>Almost all the scripting languages such as Perl, Python etc have built-in sort, but unfortunately none of them are as flexible as sort command. But one when it come to space efficiency GNU sort stands at the top. It can sort a 20Gb file with less than 2Gb memory. It is not trivial to implement so powerful a sort by yourself.</p><p>sort a space-delimited file based on its first column, then the second if the first is the same, and so on:<br />sort input.txt</p><p>sort a huge file (GNU sort ONLY):<br />sort -S 1500M -t $HOME/tmp input.txt &gt; sorted.txt</p><p>sort starting from the third column, skipping the first two columns:<br />sort +2 input.txt</p><p>sort the second column as numbers, descending order; if identical, sort the 3rd as strings, ascending order:<br />sort -k2,2nr -k3,3 input.txt</p><p>sort starting from the 4th character at column 2, as numbers:<br />sort -k2.4n input.txt</p><p>More Linxu sort command information<br /><br />If you have any sort commands you'd like to share, please add them to our comments section below. For more help, you can also type:<br /><br />man sort<br /><br />or<br /><br />sort --help<br /><br />on your Unix/Linux system.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36812/porechop-tool-for-finding-and-removing-adapters-from-oxford-nanopore-reads</guid>
	<pubDate>Tue, 29 May 2018 07:33:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36812/porechop-tool-for-finding-and-removing-adapters-from-oxford-nanopore-reads</link>
	<title><![CDATA[Porechop:  tool for finding and removing adapters from Oxford Nanopore reads]]></title>
	<description><![CDATA[<p>Porechop is a tool for finding and removing adapters from <a href="https://nanoporetech.com/">Oxford Nanopore</a> reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity.</p>
<p>Porechop also supports demultiplexing of Nanopore reads that were barcoded with the <a href="https://store.nanoporetech.com/native-barcoding-kit-1d.html">Native Barcoding Kit</a>, <a href="https://store.nanoporetech.com/pcr-barcoding-kit-96.html">PCR Barcoding Kit</a> or <a href="https://store.nanoporetech.com/rapid-barcoding-sequencing-kit.html">Rapid Barcoding Kit</a>.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Porechop" rel="nofollow">https://github.com/rrwick/Porechop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37233/rna-seq-analysis-workshop-course-materials</guid>
	<pubDate>Tue, 03 Jul 2018 08:14:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37233/rna-seq-analysis-workshop-course-materials</link>
	<title><![CDATA[RNA-seq Analysis Workshop Course Materials]]></title>
	<description><![CDATA[RNAseq can be roughly divided into two "types":

Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves our ability to reconstruct transcripts. This category would obviously include humans and most model organisms but excludes the majority of truly biologically intereting species (e.g., Hyacinth macaw);

Reference genome-free - no genome assembly for the species of interest is available. In this case one would need to assemble the reads into transcripts using de novo approaches. This type of RNAseq is as much of an art as well as science because assembly is heavily parameter-dependent and difficult to do well.
In this lesson we will focus on the Reference genome-based type of RNA seq.

http://chagall.med.cornell.edu/RNASEQcourse/<p>Address of the bookmark: <a href="http://chagall.med.cornell.edu/RNASEQcourse/" rel="nofollow">http://chagall.med.cornell.edu/RNASEQcourse/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11494/postdoc-position-at-centre-mediterraneen-de-medecine-moleculaire-nice-france</guid>
  <pubDate>Wed, 04 Jun 2014 07:20:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc position at Centre Méditerranéen de Médecine Moléculaire - Nice - France]]></title>
  <description><![CDATA[
<p>The research group of Dr. Michele Trabucchi at the Centre Méditerranéen de Médecine Moléculaire (C3M) at INSERM U1065 (University of Nice Sophia-Antipolis, France) is seeking candidates for a Postdoctoral fellow position to start on October 2014 for 3 years funded by FRM (Fondation pour la Recherche Médicale).<br />The broad interest of the lab is in understanding the expression control and function of small RNAs in activated myeloid cells (visit our webpage to check research interests and publications of the group : http://www.unice.fr/c3m/EN/Equipe10.html ). </p>

<p>The work will focus on the functional studies of small RNAs by using next-generation sequencing approaches.<br /> <br />Candidates should hold a Ph.D. degree and have strong background in bioinformatics.<br />The University of Nice Sophia-Antipolis provides a wide range of facilities and training essential for biomedical research.</p>

<p>Interested applicants should send a PDF with a cover letter stating research interests and qualifications, an updated CV, a summary of previous research experience and contact information for two references to Michele Trabucchi ( mtrabucchi@unice.fr )</p>

<p>Homepage: http://www.unice.fr/c3m/EN/Equipe10.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/28051/convert-ensembl-gtf-to-annotation-table-geneid-genesymbol-genewisechrlocation-geneclass-strand-raw</guid>
	<pubDate>Fri, 24 Jun 2016 18:08:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/28051/convert-ensembl-gtf-to-annotation-table-geneid-genesymbol-genewisechrlocation-geneclass-strand-raw</link>
	<title><![CDATA[Convert EnsEMBL GTF to Annotation table (Geneid, GeneSymbol, GeneWiseChrLocation, GeneClass, Strand) Raw]]></title>
	<description><![CDATA[<p><strong>Bash Script source:</strong></p><p>https://gist.github.com/santhilalsubhash/367befcf5216be4b1fd9</p><p>&nbsp;</p><p><strong>Information</strong>:</p><p>This script converts EnsEMBL GTF (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF">https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF</a>) file to annotation table format. It generated two files<br />1) Transcript wise chromosome location with information about transcripts (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt">https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt</a>)<br />2) Gene wise chromosome location with information about genes (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt">https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt</a>)</p><p>Note: You can download GTF files from&nbsp;<a href="http://www.ensembl.org/info/data/ftp/index.html">http://www.ensembl.org/info/data/ftp/index.html</a></p>]]></description>
	<dc:creator>EagleEye</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</guid>
	<pubDate>Sun, 08 Jun 2014 10:06:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</link>
	<title><![CDATA[Ten recommendations for creating usable bioinformatics command line software]]></title>
	<description><![CDATA[<p><span>Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used. Here I present ten recommendations for command line software author&rsquo;s tools to follow, which I believe would greatly improve the uptake and usability of their products, waste less user&rsquo;s time, and improve the quality of scientific analyses.</span></p><p>Address of the bookmark: <a href="http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer" rel="nofollow">http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer</a></p>]]></description>
	<dc:creator>RAJESH DETROJA</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2</guid>
	<pubDate>Wed, 22 Aug 2018 22:10:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2</link>
	<title><![CDATA[ComparativeGenomics Exercise2]]></title>
	<description><![CDATA[<p>COMPARATIVE MICROBIAL GENOMICS ANALYSIS WORKSHOP&nbsp; @&nbsp;cbs.dtu.dk</p><p>Free Bioinformatics workbench https://www.mn.uio.no/ifi/english/research/networks/clsi/earlier_seminars/2012/tammivesth_osloseminarfinal.pdf</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/37581" length="139956" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</guid>
	<pubDate>Fri, 19 Oct 2018 07:25:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</link>
	<title><![CDATA[BASE: a practical de novo assembler for large genomes using long NGS reads]]></title>
	<description><![CDATA[<p><span>new&nbsp;</span><em>de novo</em><span>&nbsp;assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.</span></p><p>Address of the bookmark: <a href="https://github.com/dhlbh/BASE" rel="nofollow">https://github.com/dhlbh/BASE</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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