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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/22793?offset=350</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25303/ciab-recruits-scientist-engineer-informatics-officer</guid>
  <pubDate>Sat, 28 Nov 2015 03:40:28 -0600</pubDate>
  <link></link>
  <title><![CDATA[CIAB Recruits Scientist, Engineer, Informatics Officer]]></title>
  <description><![CDATA[
<p>Center of Innovative and Applied Bioprocessing (CIAB) - Punjab</p>

<p>Center of Innovative and Applied Bioprocessing (CIAB) invites applications to recruit on vacant posts of Scientist, Associate Plant Manager/ Plant Engineer, Informatics Officer. Applications against these Government Jobs can be submitted on or before 7th January 2016.<br />CIAB Vacancy 2015 Details</p>

<p>9. Research &amp; Development – Informatics Officer<br />Qualification: M. Tech or M.E. in computer science or information technology or bioinformatics with 4 years of R&amp;D experience (after Master’s Degree) in an R&amp;D organization with work profile of large data assembly, analysis.<br />Age Limit: 45 years<br />How to Apply : Duly filled-in applications in prescribed application format along with copies of required documents should be reach to: Chief Exec</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25406/assistant-professor-bioinformatics-at-alagappa-university</guid>
  <pubDate>Thu, 03 Dec 2015 23:30:43 -0600</pubDate>
  <link></link>
  <title><![CDATA[ASSISTANT PROFESSOR Bioinformatics at ALAGAPPA UNIVERSITY]]></title>
  <description><![CDATA[
<p>ALAGAPPA UNIVERSITY<br /> Recruitment and Sarkari Naukri for the Post of ASSISTANT PROFESSOR Bioinformatics<br />Job Description UGC scale of pay is applicable. For eligibility qualifications and other norms, please refer to the ?Instructions to the Candidates? available with the application forms which can be had on payment of Rs.520/- inclusive of Rs.20/- for postage. For SC/ST, Rs.320/- inclusive of Rs.20/- for postage on enclosure of a copy of the community certificate. Payment is to be made by means of Demand Draft drawn on any nationalized bank in favour of ?The Registrar, Alagappa University? payable at Karaikudi. Candidates can also download the application form and instructions to the candidates from httpwww.alagappauniversity.ac Filled-in application should reach on or before 19.10.2015<br />Salary for Job : Rs.15600-39100+AGP Rs.6000<br />Education : Good academic record with at least 55 marks (or an equivalent grade in a point scale wherever grading system is followed) at the Masters Degree level in a relevant subject from an Indian University, or an equivalent degree from an accredited foreign university. Besides fulfilling the above qualifications, the candidate must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/SET.Notwithstanding anything contained in sub-clauses (i) and (ii) above, the candidates, who are, or have been awarded a Ph.D. degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulations 2009, shall be exempted from the requirement of the minimum eligibility condition of NET/SLET/SET for recruitment and appointment of Assistant Professor or equivalent positions in Universities/Colleges/Institutions.<br />Number of Vacancies : 02<br />Naukri Location : Other City(s) in Tamil Nadu<br />Address : KARAIKUDI ? 630 003<br />Last Date to Apply : 2015-12-04<br />Apply Process : written test/interview</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26426/genome-browser-gbrowse</guid>
	<pubDate>Fri, 19 Feb 2016 09:22:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26426/genome-browser-gbrowse</link>
	<title><![CDATA[Genome Browser : GBrowse]]></title>
	<description><![CDATA[<p>Generic Genome Browser Version 2: A Tutorial for Administrators</p>
<p>This is an extensive tutorial to take you through the main features and gotchas of configuring GBrowse as a server. This tutorial assumes that you have successfully set up Perl, GD, BioPerl and the other GBrowse dependencies. If you haven't, please see the <a href="http://gmod.org/wiki/GBrowse_2.0_HOWTO">GBrowse HOWTO</a> During most of the tutorial, we will be using the "in-memory" GBrowse database (no relational database required!) Later we will show how to set up a genome size database using the berkeleydb and MySQL adaptors.</p>
<p>More at http://elp.ucdavis.edu/tutorial/tutorial.html</p><p>Address of the bookmark: <a href="http://elp.ucdavis.edu/tutorial/tutorial.html" rel="nofollow">http://elp.ucdavis.edu/tutorial/tutorial.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26453/stacks</guid>
	<pubDate>Wed, 24 Feb 2016 15:52:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26453/stacks</link>
	<title><![CDATA[Stacks]]></title>
	<description><![CDATA[<p>Stacks is a software pipeline for building loci from short-read sequences, such as those generated on the Illumina platform. Stacks was developed to work with restriction enzyme-based data, such as RAD-seq, for the purpose of building genetic maps and conducting population genomics and phylogeography.</p>
<p>More at http://catchenlab.life.illinois.edu/stacks/</p><p>Address of the bookmark: <a href="http://catchenlab.life.illinois.edu/stacks/" rel="nofollow">http://catchenlab.life.illinois.edu/stacks/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</guid>
	<pubDate>Mon, 29 Feb 2016 17:39:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</link>
	<title><![CDATA[scikit-learn]]></title>
	<description><![CDATA[<p>Machine Learning in Python</p>
<p>Simple and efficient tools for data mining and data analysis<br> Accessible to everybody, and reusable in various contexts<br> Built on NumPy, SciPy, and matplotlib<br> Open source, commercially usable - BSD license</p>
<p>More at&nbsp;http://scikit-learn.org/stable/index.html</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://scikit-learn.org/stable/auto_examples/index.html" rel="nofollow">http://scikit-learn.org/stable/auto_examples/index.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26927/phylographer-graph-visualization-tool</guid>
	<pubDate>Wed, 06 Apr 2016 19:06:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26927/phylographer-graph-visualization-tool</link>
	<title><![CDATA[PhyloGrapher - Graph Visualization Tool]]></title>
	<description><![CDATA[<p><strong>PhyloGrapher</strong><span>&nbsp;is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).</span><strong>PhyloGrapher</strong><span>&nbsp;is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;to visualize any type of relations between elements.&nbsp;</span></p>
<p><span>More at&nbsp;http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</span></p><p>Address of the bookmark: <a href="http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html" rel="nofollow">http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27331/andi</guid>
	<pubDate>Fri, 13 May 2016 05:16:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27331/andi</link>
	<title><![CDATA[Andi]]></title>
	<description><![CDATA[<p>This is the <code>andi</code> program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because <code>andi</code> does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.</p>
<p>This readme covers all necessary instructions for the impatient to get <code>andi</code> up and running. For extensive instructions please consult the <a href="https://github.com/EvolBioInf/andi/blob/master/andi-manual.pdf">manual</a>.</p>
<p>More at https://github.com/evolbioinf/andi/</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27967/linux-command-line-exercises-for-ngs-data-processing</guid>
	<pubDate>Wed, 22 Jun 2016 07:59:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27967/linux-command-line-exercises-for-ngs-data-processing</link>
	<title><![CDATA[Linux command line exercises for NGS data processing]]></title>
	<description><![CDATA[<p>The purpose of this tutorial is to introduce students to the frequently used tools for NGS analysis as well as giving experience in writing one-liners. Copy the required files to your current directory, change directory (<code>cd</code>) to the <code>linuxTutorial</code> folder, and do all the processing inside:</p>
<pre><span>[uzi@quince-srv2 ~/]$</span> cp -r /home/opt/MScBioinformatics/linuxTutorial .
<span>[uzi@quince-srv2 ~/]$</span> cd linuxTutorial
<span>[uzi@quince-srv2 ~/linuxTutorial]$</span>
</pre>
<p>I have deliberately chosen <code>Awk</code> in the exercises as it is a language in itself and is used more often to manipulate NGS data as compared to the other command line tools such as <code>grep</code>, <code>sed</code>, <code>perl</code> etc. Furthermore, having a command on <code>awk</code> will make it easier to understand advanced tutorials such as <a href="http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/Illumina_workflow.html">Illumina Amplicons Processing Workflow</a>. <br><br> In <code>Linux</code>, we use a shell that is a program that takes your commands from the keyboard and gives them to the operating system. Most Linux systems utilize Bourne Again SHell (<code>bash</code>), but there are several additional shell programs on a typical Linux system such as <code>ksh</code>, <code>tcsh</code>, and <code>zsh</code>. To see which shell you are using, type</p>
<pre><span>[uzi@quince-srv2 ~/linuxTutorial]$</span> echo $SHELL

<span>/bin/bash
</span></pre><p>Address of the bookmark: <a href="http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/linux.html" rel="nofollow">http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/linux.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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/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>

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