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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/14215?offset=690</link>
	<atom:link href="https://bioinformaticsonline.com/related/14215?offset=690" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<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>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26850/wellcome-trustdbt-india-alliance-margdarshi-fellowships-2016</guid>
  <pubDate>Tue, 29 Mar 2016 17:47:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Wellcome Trust/DBT India Alliance Margdarshi Fellowships 2016]]></title>
  <description><![CDATA[
<p>The Wellcome Trust/DBT India Alliance invites application for the Margdarshi Fellowship scheme. The scheme provides a unique opportunity for visionary biomedical scientists to lead and nucleate a cutting edge research program in India in collaboration with Indian Host Institution(s). The potential candidates and the Host Institution are encouraged to make a synergistic effort towards establishing a centre of excellence that aims to improve the existing scientific breadth and utilizes the experience of the lead applicant for developing new research platforms. In addition to this, under this programme two eligible Indian institutions may also come together towards creating a new program under the leadership of a visionary scientist.</p>

<p>Eligibility</p>

<p>Interested applicants must</p>

<p>Have around 10 years of experience as independent investigator, and can be of any age or nationality<br />Have Sponsor(s) at not-for-profit Host Institution(s) in India, who is willing to extend the desired commitment and resources for program implementation<br />Provisions</p>

<p>The 5 year Fellowship provides</p>

<p>Generous personal support for the Fellow<br />Salary support for personnel, which may include Assistant Professors<br />Large quantum of funds for equipment, animals and consumables<br />Funds to attend scientific gatherings, for collaborative visits and to organize meetings<br />Overheads for the Host Institution<br />Process</p>

<p>A joint online application is invited from the Applicant and the Sponsor(s). The details of the scheme and the funding mechanism are available on the website at http://wellcomedbt.org/fellowshiptype/margdarshi-fellowships.</p>

<p>Application form can be accessed at https://fellowships.wellcomedbt.org/Login.aspx</p>

<p>Sponsored applications due by 2 May 2016</p>

<p>Send your inquiries to margdarshi@wellcomedbt.org</p>
]]></description>
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	<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>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26915/phd-programme-in-computational-biology</guid>
  <pubDate>Wed, 06 Apr 2016 11:47:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[Ph.D. Programme in Computational Biology]]></title>
  <description><![CDATA[
<p>Ph.D. Programme in Computational Biology</p>

<p>For students interested in frontier research at the interface of biology, computation, physics and applied mathematics</p>

<p>IMSc is a leader in India in fundamental research in theoretical physics, mathematics and theoretical computer science, with several members actively pursuing research in interdisciplinary areas including computational biology.   In 2013 IMSc started a unique Ph.D. programme in this subject, training students to apply cutting-edge computational and mathematical techniques to problems in modern biology, in collaboration with leading biology departments and institutions in India and abroad.  <br />IMSc  is an autonomous national research institute under the Department of Atomic Energy, Government of India, and a constituent institution of the Homi Bhabha National Institute (HBNI), Mumbai (a deemed university).   Ph.D. degrees will be awarded by HBNI.<br />STRUCTURE OF PROGRAMME<br />Before embarking on their research, students have three semesters of coursework, which consists of seven core courses, to be carried out at IMSc; elective courses, which may be taken at IMSc or at other institutions by mutual consent; and lab rotations, at collaborating labs in other institutions. The core coursework covers essentials of modern biology, essential techniques from physics, mathematics, statistics and computer science, physics of proteins and biomolecules, biological sequence analysis and algorithms, and systems biology. Elective coursework covers various topics in greater depth. Following the coursework and a comprehensive examination, students will embark on research leading to a Ph.D. degree.<br />Selected candidates will be research fellows at IMSc and will receive fellowships, housing or house rent allowance, and contingency grants.</p>

<p>More at http://www.imsc.res.in/graduate_programme_0</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26955/jrf-bioinformatics-at-nipgr</guid>
  <pubDate>Thu, 14 Apr 2016 13:12:42 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics at NIPGR]]></title>
  <description><![CDATA[
<p>JRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)</p>

<p>Title : “Short-Term Research Fellowship”</p>

<p>Qualification : Candidates having M.Sc./M.Tech degree (with minimum of 60% marks overall) or equivalent in Bioinformatics/Biotechnology or any other related field, are eligible to apply. Candidate having prior experience in the area of next-generation sequencing data analysis, bioinformatics, molecular analysis of plant genes, and structural data analysis will be preferred.</p>

<p>No.of Post : 01<br />How to apply</p>

<p>Application should sent to Dr. Gitanjali Yadav, Staff Scientist-IV, National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, P.O. Box NO. 10531, New Delhi - 110067 on or before 26th April 2016</p>

<p>More at http://www.nipgr.res.in/careers/vacancies_latest.php#</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26999/discovar</guid>
	<pubDate>Mon, 18 Apr 2016 11:59:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26999/discovar</link>
	<title><![CDATA[DISCOVAR]]></title>
	<description><![CDATA[<p><strong>DISCOVAR</strong> is a new variant caller and <strong>DISCOVAR <em>de novo</em></strong> a new genome assembler, both designed for state-of-the-art data. Their inputs are chosen to optimize quality while keeping costs low. Currently it takes as input Illumina reads of length 250 or longer &mdash; produced on MiSeq or HiSeq 2500 &mdash; and from a single PCR-free library. These data enable a level of completeness and continuity that was not previously possible.</p>
<p><strong>DISCOVAR</strong> can call variants on a region by region basis, potentially tiling an entire large genome. DISCOVAR variant calling is under active development and transitioning to VCF.</p>
<p><strong>DISCOVAR <em>de novo</em></strong> can generate <em>de novo</em> assemblies for both large and small genomes. It currently does not call variants.</p>
<p>More at https://www.broadinstitute.org/software/discovar/blog/?page_id=14</p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/software/discovar/blog/" rel="nofollow">https://www.broadinstitute.org/software/discovar/blog/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27257/busco-assessing-genome-assembly-and-annotation-completeness-with-benchmarking-universal-single-copy-orthologs</guid>
	<pubDate>Tue, 10 May 2016 07:46:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27257/busco-assessing-genome-assembly-and-annotation-completeness-with-benchmarking-universal-single-copy-orthologs</link>
	<title><![CDATA[BUSCO: Assessing genome assembly and annotation completeness with Benchmarking Universal Single-Copy Orthologs]]></title>
	<description><![CDATA[<ul>
<li><span>High-throughput genomics has revolutionized biological research, however, while the number of sequenced genomes grows by the day, quality assessment of the resulting assembled sequences remains complicated and mostly limited to technical measures like N50.&nbsp;</span></li>
<li></li>
<li><span>BUSCO provides measures for quantitative assessment of genome assembly, gene set, and transcriptome completeness based on evolutionarily informed expectations of gene content from near-universal single-copy orthologs selected from&nbsp;</span><a href="http://orthodb.org/">OrthoDB</a><span>.&nbsp;</span></li>
<li></li>
<li><span>BUSCO assessments are implemented in open-source software, with comprehensive lineage-specific sets of Benchmarking Universal Single-Copy Orthologs for arthropods, vertebrates, metazoans, fungi, eukaryotes, and bacteria.&nbsp;</span></li>
<li></li>
<li><span>These conserved orthologs are ideal candidates for large-scale phylogenomics studies, and the annotated BUSCO gene models built during genome assessments provide a comprehensive gene predictor training set for use as part of genome annotation pipelines.&nbsp;</span></li>
<li></li>
<li><span>BUSCO assessments offer intuitive metrics, based on evolutionarily informed expectations of gene content from hundreds of species, to gauge completeness of rapidly accumulating genomic data and satisfy an Iberian's quest for quality - "Busco calidad/qualidade".</span></li>
</ul><p>Address of the bookmark: <a href="http://busco.ezlab.org/" rel="nofollow">http://busco.ezlab.org/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27080/mrfast-micro-read-fast-alignment-search-tool</guid>
	<pubDate>Tue, 26 Apr 2016 03:50:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27080/mrfast-micro-read-fast-alignment-search-tool</link>
	<title><![CDATA[mrFAST:  Micro Read Fast Alignment Search Tool]]></title>
	<description><![CDATA[<p><span>mrFAST is a read mapper that is designed to map short reads to reference genome with a special emphasis on the discovery of structural variation and segmental duplications. mrFAST maps short reads with respect to user defined error threshold, including indels up to 4+4 bp. This manual, describes how to choose the parameters and tune mrFAST with respect to the library settings. mrFAST is designed to find&nbsp;</span><strong><span style="text-decoration: underline;">'all'</span></strong><span>&nbsp; mappings for a given set of reads, however it can return one "best" map location if the relevant parameter is invoked.</span></p>
<p><span>More at&nbsp;http://mrfast.sourceforge.net/manual.html</span></p><p>Address of the bookmark: <a href="http://mrfast.sourceforge.net/manual.html" rel="nofollow">http://mrfast.sourceforge.net/manual.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27211/srbioinformatics-analyst-ngs-ocimumbio</guid>
  <pubDate>Mon, 02 May 2016 04:41:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Sr.Bioinformatics Analyst (NGS) @ OcimumBio]]></title>
  <description><![CDATA[
<p>Sr.Bioinformatics Analyst (NGS)</p>

<p>Experience Required: 3-5 years of experience<br />No of Positions : Multiple<br />Qualifications: Candidates with minimum qualification as M.Sc Bioinformatics with 3-5  years of experience in Life sciences R&amp;D or Pharma Industry.<br />Ph.D candidates with research experience in Bioinformatics with publications in International journal and minimum 2 years of  industry experience in clinical genomics will be preferred for this position.</p>

<p>Requirement:</p>

<p>1.  Must have basic understanding of molecular biology and Genomics.<br />2. Experience in application development or must have expertise in programming using either of Perl/Python.<br />3.  Experience in statistical programming using R/Bioconductor/Matlab.<br />4. Strong concept in statistical and mathematical modelling.<br />5.  Experience in designing and developing the bioinformatics pipeline.<br />6.  Must have minimum 2+ years of hands on experience in NSG data analysis such as RNA-Seq,Exome-Seq ,Chip-Seq and downstream analysis.<br />7. Knowledge in WGS ,WES, Targeted re-sequencing,GWAS and population genomics will be preferred.<br />8. Must have experience working on opensource software/Framework and commercial software for NGS data analysis and reporting.<br />9. Should be aware of handling big data and guiding team members on multiple projects simultaneously.<br />More at http://www.ocimumbio.com/careers1/<br />10. Should have experience coordinating with different groups of clinical research scientist for various project requirements.<br />11. Ability to work as team as well as independently with minimal support.</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27261/segemehl</guid>
	<pubDate>Tue, 10 May 2016 08:10:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27261/segemehl</link>
	<title><![CDATA[segemehl]]></title>
	<description><![CDATA[<p><span>segemehl is a software to map short sequencer reads to reference genomes. Unlike other methods, segemehl is able to detect not only mismatches but also insertions and deletions. Furthermore, segemehl is not limited to a specific read length and is able to map&nbsp;primer- or polyadenylation contaminated reads correctly.&nbsp; segemehl implements a matching strategy based on enhanced suffix arrays (ESA).&nbsp;</span></p>
<p><span>More at&nbsp;http://www.bioinf.uni-leipzig.de/Software/segemehl/</span></p>
<p><span>Manual&nbsp;http://www.bioinf.uni-leipzig.de/Software/segemehl/segemehl_manual_0_1_7.pdf</span></p><p>Address of the bookmark: <a href="http://hoffmann.bioinf.uni-leipzig.de/LIFE/segemehl.html" rel="nofollow">http://hoffmann.bioinf.uni-leipzig.de/LIFE/segemehl.html</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
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