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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31568?offset=1180</link>
	<atom:link href="https://bioinformaticsonline.com/related/31568?offset=1180" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
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  <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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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</guid>
	<pubDate>Wed, 29 Nov 2017 16:44:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</link>
	<title><![CDATA[Scripts for the analysis of HGT in genome sequence data.]]></title>
	<description><![CDATA[<p><span>Scripts for the analysis of HGT in genome sequence data</span></p><p>Address of the bookmark: <a href="https://github.com/reubwn/hgt" rel="nofollow">https://github.com/reubwn/hgt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</guid>
	<pubDate>Fri, 08 Dec 2017 16:48:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</link>
	<title><![CDATA[kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome]]></title>
	<description><![CDATA[<p><span>Sept. 20, 2017 Version 3.1 released. Major upgrade. Version 3.1 fixes the problems with SNP annotation that arose when NCBI discontinued use of GI numbers. Please read carefully the Preface (page 3) and the File of annotated genomes section (pages 9-10) in the version 3.1 User Guide. Thanks to Tom Slezak for revsing the get_genbank_file3 script and to Tod Stuber (USDA) for testing version 3.1 even though he doesn't need the annotation feature. All users are encouraged to upgrade to version 3.1.&nbsp;<br></span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/ksnp/files/" rel="nofollow">https://sourceforge.net/projects/ksnp/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/34707/string-graph-based-genome-assembly-software-and-tools</guid>
	<pubDate>Tue, 19 Dec 2017 17:17:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/34707/string-graph-based-genome-assembly-software-and-tools</link>
	<title><![CDATA[String graph based genome assembly software and tools !]]></title>
	<description><![CDATA[<p>In&nbsp;<a href="https://en.wikipedia.org/wiki/Graph_theory" title="Graph theory">graph theory</a>, a&nbsp;<strong>string graph</strong>&nbsp;is an&nbsp;<a href="https://en.wikipedia.org/wiki/Intersection_graph" title="Intersection graph">intersection graph</a>&nbsp;of&nbsp;<a href="https://en.wikipedia.org/wiki/Curve" title="Curve">curves</a>&nbsp;in the plane; each curve is called a "string".&nbsp; String graphs were first proposed by E. W. Myers in a&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/21/suppl_2/ii79.full.pdf+html">2005 publication</a>.&nbsp;In&nbsp;recent&nbsp;<a href="http://genome.cshlp.org/content/early/2012/01/22/gr.126953.111">Genome Research paper</a>&nbsp;describing an innovative approach for assembling large genomes from NGS data caught our attention for several reasons. i) it give different "string graph" prospective of long lasting genome assembly problem ii) the&nbsp;paper is coauthored by Jared Simpson, the developer of&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2694472/">ABySS assembler</a>&nbsp;and Richard Durbin. iii)&nbsp;Simpson-Durbin algorithm is that it does not rely on de Bruijn graphs, and instead employs a different graph construction approach called &lsquo;string graph&rsquo;.</p><p>Following are the genome assembly tools based on string graph:</p><p>1.SGA (String Graph Assembler)&nbsp;https://github.com/jts/sga</p><p>Assembles large genomes from high coverage short read data. SGA is designed as a modular set of programs, which are used to form an assembly pipeline. SGA implements a set of assembly algorithms based on the FM-index. As the FM-index is a compressed data structure, the algorithms are very memory efficient. The SGA assembly has three distinct phases. The first phase corrects base calling errors in the reads. The second phase assembles contigs from the corrected reads. The third phase uses paired end and/or mate pair data to build scaffolds from the contigs. The output of this software is a PDF report that allows the properties of the genome and data quality to be visually explored. By providing more information to the user at the start of an assembly project, this software will help increase awareness of the factors that make a given assembly easy or difficult, assist in the selection of software and parameters and help to troubleshoot an assembly if it runs into problems.</p><p>2.&nbsp;SAGE: String-overlap Assembly of GEnomes&nbsp;https://github.com/lucian-ilie/SAGE2</p><p>SAGE, for de novo genome assembly. As opposed to most assemblers, which are de Bruijn graph based, SAGE uses the string-overlap graph. SAGE builds upon great existing work on string-overlap graph and maximum likelihood assembly, bringing an important number of new ideas, such as the efficient computation of the transitive reduction of the string overlap graph, the use of (generalized) edge multiplicity statistics for more accurate estimation of read copy counts, and the improved use of mate pairs and min-cost flow for supporting edge merging. The assemblies produced by SAGE for several short and medium-size genomes compared favourably with those of existing leading assemblers.</p><p>3. FSG: Fast String Graph</p><p>The new integrated assembler has been assessed on a standard benchmark, showing that fast string graph (FSG) is significantly faster than SGA while maintaining a moderate use of main memory, and showing practical advantages in running FSG on multiple threads. Moreover, we have studied the effect of coverage rates on the running times.</p><p>4.&nbsp;&nbsp;BASE&nbsp;https://github.com/dhlbh/BASE</p><p>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.&nbsp;BASE is a practically efficient tool for constructing contig, with significant improvement in quality for long NGS reads. It is relatively easy to extend BASE to include scaffolding.</p><p>5.&nbsp;Fermi&nbsp;https://github.com/lh3/fermi/</p><p>Fermi is a de novo assembler with a particular focus on assembling Illumina&nbsp;short sequence reads from a mammal-sized genome. In addition to the role of a&nbsp;typical assembler, fermi also aims to preserve heterozygotes which are often&nbsp;collapsed by other assemblers. Its ultimate goal is to find a minimal set of&nbsp;unitigs to represent all the information in raw reads.</p><p>If you want to learn about String Graph assembler, please read the following papers -</p><p>i)&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/21/suppl_2/ii79.full.pdf+html">The Fragment Assembly String Graph - E. W. Myers</a></p><p>This paper describes the String Graph concept.</p><p>ii)&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/26/12/i367.full#ref-20">Efficient construction of an assembly string graph using the FM-index - Jared T. Simpson and Richard Durbin</a></p><p>This earlier paper from Simpson and Durbin</p><p>iii)&nbsp;<a href="http://genome.cshlp.org/content/early/2012/01/22/gr.126953.111">Efficient de novo assembly of large genomes using compressed data structures - Jared T. Simpson and Richard Durbin</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Nayak</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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35135/alitv%E2%80%94interactive-visualization-of-whole-genome-comparisons</guid>
	<pubDate>Wed, 10 Jan 2018 07:08:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35135/alitv%E2%80%94interactive-visualization-of-whole-genome-comparisons</link>
	<title><![CDATA[AliTV—interactive visualization of whole genome comparisons]]></title>
	<description><![CDATA[<p>AliTV, which provides interactive visualization of whole genome alignments. AliTV reads multiple whole genome alignments or automatically generates alignments from the provided data. Optional feature annotations and phylo- genetic information are supported. The user-friendly, web-browser based and highly customizable interface allows rapid exploration and manipulation of the visualized data as well as the export of publication-ready high-quality figures. AliTV is freely available at&nbsp;<a href="https://github.com/AliTVTeam/AliTV">https://github.com/AliTVTeam/AliTV</a></p>
<p>https://alitvteam.github.io/AliTV/</p><p>Address of the bookmark: <a href="https://github.com/AliTVTeam/AliTV" rel="nofollow">https://github.com/AliTVTeam/AliTV</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35543/genometools-the-versatile-open-source-genome-analysis-software</guid>
	<pubDate>Wed, 07 Feb 2018 10:44:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35543/genometools-the-versatile-open-source-genome-analysis-software</link>
	<title><![CDATA[GenomeTools: The versatile open source genome analysis software]]></title>
	<description><![CDATA[<p>The&nbsp;<em>GenomeTools</em>&nbsp;genome analysis system is a&nbsp;<a href="http://genometools.org/license.html">free</a>&nbsp;collection of bioinformatics&nbsp;<a href="http://genometools.org/tools.html">tools</a>&nbsp;(in the realm of genome informatics) combined into a single binary named&nbsp;<em>gt</em>. It is based on a C library named &ldquo;libgenometools&rdquo; which consists of several modules.</p>
<p>If you are interested in gene prediction, have a look at&nbsp;<a href="http://genomethreader.org/" title="GenomeThreader gene prediction        software"><em>GenomeThreader</em></a>.</p><p>Address of the bookmark: <a href="http://genometools.org/" rel="nofollow">http://genometools.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36257/aligngraph-algorithm-for-secondary-de-novo-genome-assembly-guided-by-closely-related-references</guid>
	<pubDate>Tue, 17 Apr 2018 16:21:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36257/aligngraph-algorithm-for-secondary-de-novo-genome-assembly-guided-by-closely-related-references</link>
	<title><![CDATA[AlignGraph: algorithm for secondary de novo genome assembly guided by closely related references]]></title>
	<description><![CDATA[<p>AlignGraph is a software that extends and joins contigs or scaffolds by reassembling them with help provided by a reference genome of a closely related organism.</p>
<p>Using AlignGraph</p>
<pre><code>AlignGraph --read1 reads_1.fa --read2 reads_2.fa --contig contigs.fa --genome genome.fa --distanceLow distanceLow --distanceHigh distancehigh --extendedContig extendedContigs.fa --remainingContig remainingContigs.fa [--kMer k --insertVariation insertVariation --coverage coverage --part p --fastMap --ratioCheck --iterativeMap --misassemblyRemoval --resume]</code></pre>
<h3>&nbsp;</h3><p>Address of the bookmark: <a href="https://github.com/baoe/AlignGraph" rel="nofollow">https://github.com/baoe/AlignGraph</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
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