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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31100?offset=1270</link>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27475/polyphen-2-prediction-of-functional-effects-of-human-nssnps</guid>
	<pubDate>Mon, 23 May 2016 02:27:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27475/polyphen-2-prediction-of-functional-effects-of-human-nssnps</link>
	<title><![CDATA[PolyPhen-2: Prediction of functional effects of human nsSNPs]]></title>
	<description><![CDATA[<p><strong>PolyPhen-2</strong> (<strong>Poly</strong>morphism <strong>Phen</strong>otyping v<strong>2</strong>) is a tool which predicts possible impact of an amino acid substitution on the structure and function of a human protein using straightforward physical and comparative considerations.</p><p>Address of the bookmark: <a href="http://genetics.bwh.harvard.edu/pph2/" rel="nofollow">http://genetics.bwh.harvard.edu/pph2/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27440/stampy</guid>
	<pubDate>Fri, 20 May 2016 19:13:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27440/stampy</link>
	<title><![CDATA[Stampy]]></title>
	<description><![CDATA[<p><strong>Stampy&nbsp;</strong><span>is a package for the mapping of short reads from illumina sequencing machines onto a reference genome. It's recommended for most workflows, including those for genomic resequencing, RNA-Seq and Chip-seq. Stampy excels in the mapping of reads containing that contain sequence variation relative to the reference, in particular for those containing insertions or deletions.</span></p><p>Address of the bookmark: <a href="http://www.well.ox.ac.uk/project-stampy" rel="nofollow">http://www.well.ox.ac.uk/project-stampy</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27461/maftools</guid>
	<pubDate>Sat, 21 May 2016 22:40:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27461/maftools</link>
	<title><![CDATA[mafTools]]></title>
	<description><![CDATA[<p><span>Bioinformatics tools for dealing with Multiple Alignment Format (MAF) files.</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/mafTools" rel="nofollow">https://github.com/dentearl/mafTools</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27473/project-assistantjunior-research-fellow-position-at-centre-of-biomedical-research-sanjay-gandhi-postgraduate-institute-of-medical-sciences-campus-lucknow</guid>
  <pubDate>Mon, 23 May 2016 01:31:29 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Assistant/Junior Research Fellow Position at  Centre of Biomedical Research, Sanjay Gandhi Postgraduate Institute of Medical Sciences Campus, Lucknow.]]></title>
  <description><![CDATA[
<p>Applications are invited from eligible candidates willing to join in a Department of Science and Technology (DST) project entitled “"Mapping neural regions involved in reading process in skilled adult Deaf reader: From neuroimaging perspective (functional Magnetic Resonance Imaging (fMRI) and Diffuse Tensor Imaging (DTI.)" as a Project Assistant/Junior Research Fellow (JRF) at Centre of Biomedical Research, Sanjay Gandhi Postgraduate Institute of Medical Sciences Campus, Lucknow.</p>

<p>Essential Qualification:</p>

<p>1. Master's degree in Bioinformatics / Computer Applications / Cognitive Science /Neuroscience/ Neuropsychology or equivalent. (Advantage will be given to NET JRF qualified candidate) Additional</p>

<p>Desirable Skills:</p>

<p>1) Programming skills (e.g., C++, Matlab, Python) 2) Experience/competent in working Window and Linux based programme.</p>

<p>Please mail your CV and covering letter to dr.uttam.kumar@gmail.com.</p>

<p>To know more about lab works please visit http://uttambrainlab.co.in/lab/.</p>

<p>Last date: 15/06/16</p>

<p>Advertisement: http://cbmr.res.in/wp-content/uploads/2016/05/Advertisement-19-5-2016.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27554/jrf-bioinformatics-at-actrec-navi-mumbai</guid>
  <pubDate>Mon, 30 May 2016 03:24:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics at ACTREC, Navi Mumbai]]></title>
  <description><![CDATA[
<p>No. ACTREC/Advt./23/2016<br />JRF Bioinformatics recruitment in ACTREC (On contract Basis- Primeone Workforce Pvt. Ltd.)<br />Title : “Investigating the molecular basis of CaM/c-FLIP interaction to design specific c-FLIP inhibitor for modulating its anti-apoptotic function”.<br />Qualification : Master’s degree in bioinformatics, biochemistry, biotechnology and biological sciences from a recognized university with not less than 55% aggregate marks. Experience: Prior experience in modelling, protein-protein/ligand docking, Molecular dynamics simulation required. Knowledge in database development will be preferred.   </p>

<p>Pay Scale : Rs. 32,500/- <br />How to apply<br />Candidates fulfilling these requirements should pre-register by sending their application in the prescribed format with recent CV and contact details of 2 referees by e-mail to  ‘program.office@actrec.gov.in’ latest by  17.00 hrs on 23-06-2016. The interviews would be held on 27-06-2016 and only pre-registered candidates will be eligible to appear for interview. Candidates should report between 09.30 to 10.00 a.m. in Steno Pool,  3rd floor, Khanolkar Shodhika, ACTREC, Kharghar, Navi Mumbai.</p>

<p>More at http://www.actrec.gov.in/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/27695/the-kingsley-lab</guid>
  <pubDate>Fri, 03 Jun 2016 09:55:10 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Kingsley Lab]]></title>
  <description><![CDATA[
<p>The Molecular Basis of Vertebrate Evolution. Naturally occurring species show spectacular differences in morphology, physiology, behavior, disease susceptibility, and life span. Although the genomes of many organisms have now been completely sequenced, Kingsley lab still know relatively little about the specific DNA sequence changes that underlie interesting species-specific traits. Kingsley lab laboratory is using a combination of genetic and genomic approaches to identify the detailed molecular mechanisms that control evolutionary change in vertebrates.</p>
]]></description>
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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>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28164/greengenes-database</guid>
	<pubDate>Wed, 29 Jun 2016 10:03:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28164/greengenes-database</link>
	<title><![CDATA[Greengenes database]]></title>
	<description><![CDATA[<p>The greengenes web application provides access to the 2011 version of the greengenes 16S rRNA gene sequence alignment for browsing, blasting, probing, and downloading. The data and tools presented by greengenes can assist the researcher in choosing phylogenetically specific probes, interpreting microarray results, and aligning/annotating novel sequences. If you are an ARB user, you can use greengenes to keep your own local database current.</p><p>Address of the bookmark: <a href="http://greengenes.lbl.gov/cgi-bin/nph-index.cgi" rel="nofollow">http://greengenes.lbl.gov/cgi-bin/nph-index.cgi</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27961/nearhgt</guid>
	<pubDate>Wed, 22 Jun 2016 05:41:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27961/nearhgt</link>
	<title><![CDATA[NearHGT]]></title>
	<description><![CDATA[<p>Horizontal gene transfer (HGT), the transfer of genetic material between organisms, is crucial for genetic innovation and the evolution of genome architecture. Existing HGT detection algorithms rely on a strong phylogenetic signal distinguishing the transferred sequence from ancestral (vertically derived) genes in its recipient genome. Detecting HGT between closely related species or strains is challenging, as the phylogenetic signal is usually weak and the nucleotide composition is normally nearly identical. Nevertheless, there is a great importance in detecting HGT between congeneric species or strains, especially in clinical microbiology, where understanding the emergence of new virulent and drug-resistant strains is crucial, and often time-sensitive.</p>
<p>We developed a novel, self-contained technique named&nbsp;<em>Near HGT</em>, based on the&nbsp;<em>synteny index</em>, to measure the divergence of a gene from its native genomic environment and used it to identify candidate HGT events between closely related strains. The method confirms candidate transferred genes based on the&nbsp;<em>constant relative mutability</em>&nbsp;(CRM). Using CRM, the algorithm assigns a confidence score based on &ldquo;unusual&rdquo; sequence divergence. A gene exhibiting exceptional deviations according to both synteny and mutability criteria, is considered a validated HGT product. We first employed the technique to a set of three&nbsp;<em>E. coli</em>&nbsp;strains and detected several highly probable horizontally acquired genes. We then compared the method to existing HGT detection tools using a larger strain data set.</p>
<p>When combined with additional approaches our new algorithm provides richer picture and brings us closer to the goal of detecting all newly acquired genes in a particular strain.</p>
<p><strong>Availability:</strong><span>&nbsp;The method is publicly available at</span><a href="http://research.haifa.ac.il/~ssagi/software/nearHGT.zip">http://research.haifa.ac.il/~ssagi/software/nearHGT.zip</a></p><p>Address of the bookmark: <a href="http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004408" rel="nofollow">http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004408</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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