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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/13267?offset=530</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26250/research-fellow-bioinformatics-at-central-university-of-rajasthan</guid>
  <pubDate>Tue, 02 Feb 2016 00:04:50 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Fellow Bioinformatics at Central University of Rajasthan]]></title>
  <description><![CDATA[
<p>Research Fellow Bioinformatics</p>

<p>Eligibility : MSc(Bio-Chemistry, Bio-Informatics, Bio-Tech)<br />Location : Ajmer<br />Last Date : 13 Feb 2016<br />Hiring Process : Face to Face Interview<br />Central University of Rajasthan</p>

<p>Research Fellow Job vacancies in Central University of Rajasthan</p>

<p>Project Title : “Development of natural product derived febrifugine ananlogues as a novel therapeutics against visceral leishmaniasis”</p>

<p>No. of Post : 01</p>

<p>Qualification : Master of Biochemistry, Biotechnology, Bioinformatics and related biological sciences with minimum 55%, Age limit as per government rule.</p>

<p>Desirable Experience : Candidates with experience in cell culture, Chemoinformatics, and Parasitology will be preferred.    </p>

<p>Fellowship : Rs. 25,000/- p.m. consolidated for NET qualified (14,000/- p.m. consolidated for Non-NET)<br />How to apply</p>

<p>The candidates may apply on a plain paper, along with their curriculum vitae (including name, date of birth, academic qualification starting from 10th class, summary of research experience, email id, phone number and passport size photograph) and email to vkprajapati@curaj.ac.in or post the hard copy to the Dr. Vijay Kumar Prajapati PI, DST-SERB Project (YSS/2015/000716), Department of Biochemistry, School of Life Sciences, Central University of Rajasthan, Bandarsindri, Dist- Ajmer, Rajasthan, 305 817 on or before 13th February 2016.</p>

<p>More at http://www.curaj.ac.in/Default.aspx?PageId=241</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26432/summer-2016</guid>
  <pubDate>Sun, 21 Feb 2016 06:17:55 -0600</pubDate>
  <link></link>
  <title><![CDATA[Summer 2016]]></title>
  <description><![CDATA[
<p>REU at Fordham University- Summer 2016</p>

<p>An NSF-funded REU to study Y-chromosome diversity and sex-biased dispersal in wild brown rats (Rattus norvegicus) is available in the Munshi-South Lab at Fordham University. Our lab is currently investigating rat evolution at scales ranging from landscape genetics of individual cities to global patterns of diversity. Development of resources for investigating Y-chromosome diversity will support many of these studies. The REU student will work with the lab to bioinformatically identify Y-chromosome SNPs, design SNPtype assays,<br />extract DNA, genotype samples, and analyze data.</p>

<p>We seek applicants interested in bioinformatics, evolutionary biology, and related disciplines.  Applicants must have taken a college-level genetics course.  This REU will require attention to detail, reliability, independence, and critical thinking.</p>

<p>This position is based at Fordham University's field station, the Louis Calder Center, in Armonk, NY. The Calder Center is located approximately 25 miles north of New York City in a protected woodland area. Housing<br />will be provided at the Calder Center for the duration of the REU (May 23 to Aug 12, 2016). Additionally, the student will receive a $6,000 stipend. The selected student will participate in professional development activities through the Calder Centers REU program, including presentation of results at a research colloquium at the end of the summer.</p>

<p>To apply, please send a one page personal statement about your scientific interests and how this REU will support your professional goals, unofficial transcripts including a list of Spring 2016 courses, and names of two professional references (including title, address, phone number, and email address) as a single pdf (with your last name in the file name) to Dr. Jason Munshi-South (jmunshisouth@fordham.edu).</p>

<p>Applications are due March 4th, 2016.</p>

<p>Jason Munshi-South</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26543/breakseq2</guid>
	<pubDate>Mon, 29 Feb 2016 17:45:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26543/breakseq2</link>
	<title><![CDATA[BreakSeq2]]></title>
	<description><![CDATA[<p>Ultrafast and accurate nucleotide-resolution analysis of structural variants</p>
<p>More at http://bioinform.github.io/breakseq2/</p>
<p>Download BreakSeq2</p>
<p>Latest version: https://github.com/bioinform/breakseq2/archive/2.2.tar.gz<br><br>For other versions, see "releases". https://github.com/bioinform/breakseq2/releases</p><p>Address of the bookmark: <a href="http://bioinform.github.io/breakseq2/" rel="nofollow">http://bioinform.github.io/breakseq2/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</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/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</guid>
	<pubDate>Sat, 21 May 2016 22:42:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</link>
	<title><![CDATA[Bpipe - a tool for running and managing bioinformatics pipelines]]></title>
	<description><![CDATA[<p>Bpipe provides a platform for running big bioinformatics jobs that consist of a series of processing stages - known as 'pipelines'.</p>
<ul>
<li>January 20th, 2016 - New! Bpipe 0.9.9 released!</li>
<li>Download <a href="http://download.bpipe.org/versions/bpipe-0.9.9.tar.gz">latest</a>, <a href="http://download.bpipe.org">all</a></li>
<li><a href="http://docs.bpipe.org">Documentation</a></li>
<li><a href="https://groups.google.com/forum/#%21forum/bpipe-discuss">Mailing List</a> (Google Group)</li>
</ul>
<p>Bpipe has been published in <a href="http://bioinformatics.oxfordjournals.org/content/early/2012/04/11/bioinformatics.bts167.abstract">Bioinformatics</a>! If you use Bpipe, please cite:</p>
<p><em>Sadedin S, Pope B &amp; Oshlack A, Bpipe: A Tool for Running and Managing Bioinformatics Pipelines, Bioinformatics</em></p><p>Address of the bookmark: <a href="http://docs.bpipe.org/" rel="nofollow">http://docs.bpipe.org/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2726/comparison-of-short-read-de-novo-alignment-algorithms</guid>
	<pubDate>Wed, 21 Aug 2013 07:56:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2726/comparison-of-short-read-de-novo-alignment-algorithms</link>
	<title><![CDATA[Comparison of Short Read De Novo Alignment Algorithms]]></title>
	<description><![CDATA[<p>Excellent article to introduce different sequencing methods along with tools for de novo assembly of sequencing reads and their relevant references.</p>
<p>Title:&nbsp;<strong>Comparison of Short Read De Novo Alignment Algorithms&nbsp;</strong></p>
<p>Author<strong>: Nikhil Gopal</strong></p><p>Address of the bookmark: <a href="http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf" rel="nofollow">http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads</guid>
	<pubDate>Mon, 30 Apr 2018 04:38:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads</link>
	<title><![CDATA[ALPACA: A hybrid strategy for assembly of genomic DNA shotgun sequencing reads.]]></title>
	<description><![CDATA[<p><span>ALPACA requires Celera Assembler 8.3 or later. It is recommended to build Celera Assembler from source. (Why? The pre-built binaries CA_8.3rc1 and CA8.3rc2 will work for any large data set.&nbsp;</span></p>
<p><span>Detail paper at&nbsp;https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3927-8</span></p><p>Address of the bookmark: <a href="https://github.com/VicugnaPacos/ALPACA" rel="nofollow">https://github.com/VicugnaPacos/ALPACA</a></p>]]></description>
	<dc:creator>Seema Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26752/rna-seq-de-novo-assembly-using-trinity</guid>
	<pubDate>Wed, 23 Mar 2016 05:53:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26752/rna-seq-de-novo-assembly-using-trinity</link>
	<title><![CDATA[RNA-Seq De novo Assembly Using Trinity]]></title>
	<description><![CDATA[<p>Trinity, developed at the <a href="http://www.broadinstitute.org">Broad Institute</a> and the <a href="http://www.cs.huji.ac.il">Hebrew University of Jerusalem</a>, represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data. Trinity combines three independent software modules: Inchworm, Chrysalis, and Butterfly, applied sequentially to process large volumes of RNA-seq reads. Trinity partitions the sequence data into many individual de Bruijn graphs, each representing the transcriptional complexity at at a given gene or locus, and then processes each graph independently to extract full-length splicing isoforms and to tease apart transcripts derived from paralogous genes. Briefly, the process works like so:</p>
<ul>
<li>
<p><em>Inchworm</em> assembles the RNA-seq data into the unique sequences of transcripts, often generating full-length transcripts for a dominant isoform, but then reports just the unique portions of alternatively spliced transcripts.</p>
</li>
<li>
<p><em>Chrysalis</em> clusters the Inchworm contigs into clusters and constructs complete de Bruijn graphs for each cluster. Each cluster represents the full transcriptonal complexity for a given gene (or sets of genes that share sequences in common). Chrysalis then partitions the full read set among these disjoint graphs.</p>
</li>
<li>
<p><em>Butterfly</em> then processes the individual graphs in parallel, tracing the paths that reads and pairs of reads take within the graph, ultimately reporting full-length transcripts for alternatively spliced isoforms, and teasing apart transcripts that corresponds to paralogous genes.</p>
</li>
</ul>
<p>More at https://github.com/trinityrnaseq/trinityrnaseq/wiki</p>
<p>......................................................................................................................................</p>
<p>Download Trinity <a href="https://github.com/trinityrnaseq/trinityrnaseq/releases">here</a>.</p>
<p>Build Trinity by typing 'make' in the base installation directory.</p>
<p>Assemble RNA-Seq data like so:</p>
<pre><code> Trinity --seqType fq --left reads_1.fq --right reads_2.fq --CPU 6 --max_memory 20G 
</code></pre>
<p>Find assembled transcripts as: 'trinity_out_dir/Trinity.fasta'</p><p>Address of the bookmark: <a href="https://github.com/trinityrnaseq/trinityrnaseq/wiki" rel="nofollow">https://github.com/trinityrnaseq/trinityrnaseq/wiki</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26911/raca-reference-assisted-chromosome-assembly</guid>
	<pubDate>Wed, 06 Apr 2016 09:29:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26911/raca-reference-assisted-chromosome-assembly</link>
	<title><![CDATA[RACA: Reference-Assisted Chromosome Assembly]]></title>
	<description><![CDATA[<p>Rreference-Assisted Chromosome Assembly (RACA), an algorithm to reliably order and orient sequence scaffolds generated by NGS and assemblers into longer chromosomal fragments using comparative genome information and paired-end reads.</p>
<p>http://www.ncbi.nlm.nih.gov/pubmed/23307812</p>
<p>http://bioen-compbio.bioen.illinois.edu/RACA/</p><p>Address of the bookmark: <a href="http://bioen-compbio.bioen.illinois.edu/RACA/" rel="nofollow">http://bioen-compbio.bioen.illinois.edu/RACA/</a></p>]]></description>
	<dc:creator>Priya Singh</dc:creator>
</item>

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