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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27821?offset=510</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29130/gage-genome-assembly-gold-standard-evaluation</guid>
	<pubDate>Wed, 07 Sep 2016 07:35:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29130/gage-genome-assembly-gold-standard-evaluation</link>
	<title><![CDATA[GAGE : Genome Assembly Gold-standard Evaluation]]></title>
	<description><![CDATA[<p><span>GAGE is an evaluation of the very latest large-scale genome assembly algorithms. We have organized this "bake-off" as an attempt to produce a realistic assessment of genome assembly software in a rapidly changing field of next-generation sequencing. The main results of GAGE have now been published in the journal Genome Research:&nbsp;</span><a href="http://genome.cshlp.org/content/early/2012/01/12/gr.131383.111">GAGE: A critical evaluation of genome assemblies and assembly algorithms</a><span>.</span></p>
<p><span>http://genome.cshlp.org/content/early/2012/01/12/gr.131383.111</span></p><p>Address of the bookmark: <a href="http://gage.cbcb.umd.edu/index.html" rel="nofollow">http://gage.cbcb.umd.edu/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29217/bioinformatics-openings-at-sri-venkateswara-college-university-of-delhi</guid>
  <pubDate>Tue, 20 Sep 2016 05:43:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics openings at Sri Venkateswara College, University of Delhi]]></title>
  <description><![CDATA[
<p>Bioinformatics center</p>

<p>Sri Venkateswara College (University of Delhi)</p>

<p>New Delhi- 110021</p>

<p>1. Junior Research Fellow (1 Post)</p>

<p>Applications are invited for the post of Junior Research Fellow (JRF) under DST funded project which is purely temporary and is strictly for project duration only.</p>

<p>Title of project</p>

<p>No. of post</p>

<p>Remuneration (Rs.)</p>

<p>“Computational assisted Design and Synthesis of Novel Antimalarial Agents Embodying Structural Diversity Suitable for Protease Inhibitors”</p>

<p>(One)</p>

<p>Fellowship and HRA as per DST guidelines</p>

<p>Qualification</p>

<p>Post Graduate Degree in Basic Science (M.Sc./M.Tech in Bioinformatics/Biophysics) from a recognized University in India or abroad with at least 55% marks with NET qualification or Graduate Degree in Professional Course with NET Qualification or Post Graduate Degree in Professional Course.</p>

<p>Desirable</p>

<p>Fair knowledge of Computer Aided Drug Designing (CADD), Protein Structure modeling, molecular docking, and simulations are preferable.</p>

<p>2. Traineeship (1 Post)</p>

<p>Applications are invited for the position of traineeship in DBT-BTISnet funded Bioinformatics Infrastructure Facility (BIF) to carry out project work in the area of Bioinformatics.</p>

<p>Qualification</p>

<p>Applicant should be possess PG degree/PG diploma in Bioinformatics for traineeship. The traineeship is awarded for a period of six months from the date of joining and is not extendable. The selected candidates are entitled to receive a stipend of Rs. 8000/- per month (consolidate) for a period of 6 months.</p>

<p>=====================================================================</p>

<p>3. Studentship (1 Post)</p>

<p>Applications are invited for the position of Studentship in DBT-BTISnet funded Bioinformatics Infrastructure Facility (BIF) to carry out project work in the area of Bioinformatics.</p>

<p>Qualification</p>

<p>Candidates pursuing the Final Year of Post Graduate Degree in Basic Science (M.Sc.) or Post Graduate/ Graduate Degree in Professional Course (M.Tech/B.Tech) in Bioinformatics from a recognized University in India or abroad. The selected candidates are entitled to receive a stipend of Rs. 8000/- per month (consolidate) for a period of 6 months.</p>

<p>How to Apply?</p>

<p>Applicants are required to send applications on plain paper, stating the name, address, date of birth, educational qualification, experience and Institute, along with attested photocopies of mark sheets and certificates etc. by September 20, 2016 to:</p>

<p>The Coordinator</p>

<p>Bioinformatics Center, Sri Venkateswara College</p>

<p>Benito Juarez Road, Dhaula Kuan, New Delhi- 110021</p>

<p>Applications may also be sent by email to contact@bic-svc.ac.in. Strictly mention "Application for JRF, Traineeship or Studentship" in the subject line as the case may be.</p>

<p>Short listed candidates will be called for an interview. Canvassing in any form will be a disqualification. No TA/DA will be paid either for attending the interview or joining the post.</p>

<p>For more details visit our lab webpage: http://www.bic-svc.ac.in</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29272/decipher</guid>
	<pubDate>Fri, 30 Sep 2016 09:33:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29272/decipher</link>
	<title><![CDATA[DECIPHER]]></title>
	<description><![CDATA[<p>DECIPHER is a software toolset that can be used to maintain, analyze, and decipher large amounts of DNA sequence data. To install DECIPHER, see the <a href="http://DECIPHER.cee.wisc.edu/Download.html">Downloads</a> page.<br><br> To begin using DECIPHER read the "Getting Started DECIPHERing" tutorial. Refer to the PDF documents below for instructions on how to use DECIPHER for various tasks.</p><p>Address of the bookmark: <a href="http://decipher.cee.wisc.edu/Documentation.html" rel="nofollow">http://decipher.cee.wisc.edu/Documentation.html</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29282/cosmic</guid>
	<pubDate>Sat, 01 Oct 2016 15:04:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29282/cosmic</link>
	<title><![CDATA[COSMIC]]></title>
	<description><![CDATA[<p>The accurate description and annotation of structural variants can be complex. &nbsp;This is due to the different resolution that variants are reported from traditional&nbsp;cytogenetic coordinates down to the actual base pair positions. Furthermore, multiple&nbsp;rearrangements in a single area of the genome can make cataloguing and interpreting&nbsp;their effects challenging.&nbsp;</p>
<p>The Rearrangement Overview page describes the one or more breakpoints which make up a structural&nbsp;variant. A breakpoint is defined as a region or point where the sample sequence has altered&nbsp;from the reference sequence. Minimum interpretation is made of this data. One variant event&nbsp;can consist of one or multiple breakpoints. The Syntax (shown above the table) gives a detailed description of the variant and its location &nbsp;(e.g. chr11:g.36585230_76606619del, a deletion of&nbsp;roughly 40Mb on chromosome 11). Syntax is based on HGVS mutation nomenclature recommendations&nbsp;[http://www.hgvs.org/rec.html].&nbsp;</p>
<p>http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview</p><p>Address of the bookmark: <a href="http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview" rel="nofollow">http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29382/virmet</guid>
	<pubDate>Mon, 10 Oct 2016 08:27:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29382/virmet</link>
	<title><![CDATA[VirMet]]></title>
	<description><![CDATA[<p>Watch out: only a few files are counted in coverage statistics.</p>
<p>Full documentation on&nbsp;<a href="http://virmet.rtfd.org/en/latest/">Read the Docs</a>.</p>
<p>A set of tools for viral metagenomics.</p>
<p>virmet is called with a command subcommand syntax:&nbsp;<code>virmet fetch --viral n</code>, for example, downloads the bacterial database. Other available subcommands so far are</p>
<ul>
<li><code>fetch</code>&nbsp;download genomes</li>
<li><code>update</code>&nbsp;update viral/bacterial database</li>
<li><code>index</code>&nbsp;index genomes</li>
<li><code>wolfpack</code>&nbsp;analyze a Miseq run</li>
<li><code>covplot</code>&nbsp;plot coverage for a specific organism</li>
</ul>
<p>A short help is obtained with&nbsp;<code>virmet subcommand -h</code>.</p>
<p>More at&nbsp;https://github.com/ozagordi/VirMet</p><p>Address of the bookmark: <a href="https://github.com/ozagordi/VirMet" rel="nofollow">https://github.com/ozagordi/VirMet</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29574/beagle</guid>
	<pubDate>Thu, 27 Oct 2016 11:19:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29574/beagle</link>
	<title><![CDATA[Beagle]]></title>
	<description><![CDATA[<p>Beagle is a software package that performs genotype calling, genotype phasing, imputation of ungenotyped markers, and identity-by-descent segment detection.</p>
<p>Beagle version 4.1 has a more accurate genotype phasing algorithm and a very fast and accurate genotype imputation algorithm. Version 4.1 also has several changes to the command line arguments which are described in the&nbsp;<a href="http://faculty.washington.edu/browning/beagle/release_notes" target="_blank">release notes</a>. The "ped" argument has no effect in version 4.1. If your data contains nuclear families and you want to model the parent-offspring relationships when phasing genotypes, please use&nbsp;<a href="https://faculty.washington.edu/browning/beagle/b4_0.html">version 4.0</a>.</p>
<p>If you use Beagle 4.1 in a published analysis, please report the program version and cite the appropriate article.</p>
<p>The citation for Beagle's phasing algorithm is:</p>
<p>S R Browning and B L Browning (2007) Rapid and accurate haplotype phasing and missing data inference for whole genome association studies by use of localized haplotype clustering. Am J Hum Genet 81:1084-1097.<a href="http://dx.doi.org/doi:10.1086/521987" target="_blank">doi:10.1086/521987</a></p>
<p>The citation for Beagle's genotype imputation algorithm is:</p>
<p>B L Browning and S R Browning (2016). Genotype imputation with millions of reference samples. Am J Hum Genet 98:116-126.<a href="http://dx.doi.org/doi:10.1016/j.ajhg.2015.11.020" target="_blank">doi:10.1016/j.ajhg.2015.11.020</a></p>
<p>The citation for Beagle's IBD detection algorithm is:</p>
<p>B L Browning and S R Browning (2013). Improving the accuracy and efficiency of identity-by-descent detection in population data. Genetics 194(2):459-71.<a href="http://dx.doi.org/doi:10.1534/genetics.113.150029" target="_blank">doi:10.1534/genetics.113.150029</a></p><p>Address of the bookmark: <a href="http://faculty.washington.edu/browning/beagle/beagle.html" rel="nofollow">http://faculty.washington.edu/browning/beagle/beagle.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29586/eforgev12</guid>
	<pubDate>Fri, 28 Oct 2016 09:06:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29586/eforgev12</link>
	<title><![CDATA[eFORGE.v1.2]]></title>
	<description><![CDATA[<p><span>The eFORGE tool provides a method to view the tissue specific regulatory component of a set of EWAS DMPs. eFORGE analysis takes a set of DMPs, such as those hits above genome-wide significance threshold in an EWAS study, and analyses whether there is enrichment for overlap of putative functional elements compared to matched background DMPs. It assesses enrichment on a per cell type basis, since functional elements are differentially active in different cell types, and hence can expose tissue-specific signals of enrichment for the given test DMP set. This can reveal the sites of action underlying the EWAS signal, and provide confirmation of the validity of the EWAS where a tissue-specific mechanism is known or expected for the phenotype. Conversely unknown tissue involvements can also be revealed.</span></p><p>Address of the bookmark: <a href="http://eforge.cs.ucl.ac.uk/eFORGE.v1.2/?documentation" rel="nofollow">http://eforge.cs.ucl.ac.uk/eFORGE.v1.2/?documentation</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29614/art-set-of-simulation-tools</guid>
	<pubDate>Thu, 03 Nov 2016 08:28:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29614/art-set-of-simulation-tools</link>
	<title><![CDATA[ART: Set of Simulation Tools]]></title>
	<description><![CDATA[<p>ART is a set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina's Solexa, Roche's 454 and Applied Biosystems' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART was used as a primary tool for the simulation study of the <span><a href="http://www.1000genomes.org/" target="_blank">1000 Genomes Project<span></span></a></span> . ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format. ART can be used together with genome variants simulators (e.g. <span><a href="http://bioinform.github.io/varsim/" target="_blank">VarSim<span></span></a></span>) for evaluating variant calling tools or methods.</p><p>Address of the bookmark: <a href="http://www.niehs.nih.gov/research/resources/software/biostatistics/art/" rel="nofollow">http://www.niehs.nih.gov/research/resources/software/biostatistics/art/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</guid>
	<pubDate>Fri, 04 Nov 2016 10:48:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</link>
	<title><![CDATA[R Graphs !!]]></title>
	<description><![CDATA[<p><span>The blog is a collection of script examples with example data and output plots. R produce excellent quality graphs for data analysis, science and business presentation, publications and other purposes. Self-help codes and examples are provided. Enjoy nice graphs !!</span></p><p>Address of the bookmark: <a href="http://rgraphgallery.blogspot.be/" rel="nofollow">http://rgraphgallery.blogspot.be/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29652/bioistats-ppt</guid>
	<pubDate>Tue, 08 Nov 2016 07:09:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29652/bioistats-ppt</link>
	<title><![CDATA[Bioistats PPT]]></title>
	<description><![CDATA[<p>Basics concepts of&nbsp;Probability: The Study of Randomness</p><p>Biostatistics is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine, pharmacy, agriculture and fishery; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results. A major branch of this is medical biostatistics, which is exclusively concerned with medicine and health.</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29652" length="1663809" type="application/pdf" />
</item>

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