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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37257?offset=360</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6961/research-assistant-national-bureau-of-animal-genetic-resources</guid>
  <pubDate>Tue, 03 Dec 2013 06:17:34 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Assistant @ NATIONAL BUREAU OF ANIMAL GENETIC RESOURCES]]></title>
  <description><![CDATA[
<p>NATIONAL BUREAU OF ANIMAL GENETIC RESOURCES<br />Near Basant Vihar G.T. Road Bypass<br />P.O. Box No.129, Karnal-132001 (Haryana)</p>

<p>WALK-IN-INTERVIEW</p>

<p>A walk-in-Interview is proposed to be held at National Bureau of Animal Genetic Resources, Karnal (Haryana)-132001 at 11:30 AM on 18.12.2013 to select One RA and One SRF as per details given below:</p>

<p>1. One post of Research Associate under DBT sponsored Support under BIPP for the “SanGenix: A comprehensive Next Generation Sequence (NGS) data analysis solution” as Grants in AID. Thepost duration is Upto 31st March 2015 or earlier.</p>

<p>2. One post of Senior Research Fellow under NAIP (Component-4) Bioprospecting of genes and allele mining for abiotic stress tolerance. The post duration is Upto 31st March 2014 or earlier</p>

<p>Essential Qualifications: Ph.D. in Bioinformatics/ Computer Application or<br />First Class Masters degree in Bioinformatics/ Computer Application with two years experience as evidenced by Publications.</p>

<p>Desirable: Experience in the field of handling Next generation Sequencing Data.</p>

<p>Emolument: Rs. 22,000/- per month + HRA as per admissibility</p>

<p>Age Limit:</p>

<p>40 years for Men<br />45 years for women as on date of interview</p>

<p>Research Associate: ONE</p>

<p>Duration of engagement: Upto</p>

<p>31st March 2015 or earlier &amp; Coterminus with the project</p>

<p>Responsibilities: To help the PI for Beta testing and development of the SanGenix Tool for NGS data.</p>

<p>Essential Qualifications: First Class Masters’ degree in Bioinformatics/Biotechnology.</p>

<p>Desirable: Experience in the field of Biotechnology/ Bioinformatics</p>

<p>Emoluments:</p>

<p>Rs. 16,000/- per month + HRA as per admissibility.<br />Senior Research Fellow: ONE<br />Duration of engagement: Upto 31st March 2014 or earlier &amp; Coterminus with the project</p>

<p>Age Limit</p>

<p>35 years for men<br />40 years for women as on date of interview</p>

<p>Note: Relaxation in age will be admissible for SC/ST &amp; OBC candidates as per Govt. of India /ICAR norms</p>

<p>1. The applicants must bring with them original documents and brief of research work done during post graduation along with a set of photocopy and latest two passport size photographs.<br />2. A panel of selected candidates will also be made which may be utilized for filling of positions of shorter durations in future if demand arises.<br />3. Experience certificate in original, if any 4. The above positions are purely on temporary basis and are co-terminus with the project. No TA/DA will be paid to attend the interview.<br />5. Any other clarifications can be had on the date of interview.<br />6. The Director’s decision will be final and binding on all respects.</p>

<p>Advertisement: http://210.212.93.85/rasrfadvertise.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12787/integrative-genomics-viewer-igv-tutorial</guid>
	<pubDate>Sat, 12 Jul 2014 15:16:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12787/integrative-genomics-viewer-igv-tutorial</link>
	<title><![CDATA[Integrative Genomics Viewer (IGV) tutorial]]></title>
	<description><![CDATA[<p>The <a href="http://www.broadinstitute.org/igv/">Integrative Genomics Viewer (IGV)</a> from the Broad Center allows you to view several types of data files involved in any NGS analysis that employs a reference genome, including how reads from a dataset are mapped, gene annotations, and predicted genetic variants.</p>
<p>http://www.broadinstitute.org/igv/</p><p>Address of the bookmark: <a href="https://wikis.utexas.edu/display/bioiteam/Integrative+Genomics+Viewer+%28IGV%29+tutorial" rel="nofollow">https://wikis.utexas.edu/display/bioiteam/Integrative+Genomics+Viewer+%28IGV%29+tutorial</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17873/postdoc-position-in-protein-annotation-and-machine-learning-paris-france</guid>
  <pubDate>Sat, 04 Oct 2014 08:10:45 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc position in protein annotation and machine learning - Paris, France]]></title>
  <description><![CDATA[
<p>We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of Paris.</p>

<p>Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.</p>

<p>This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.</p>

<p>The postdoc will be payed under a contract of Ingénieur de Recherche lasting 3.5 years and it is available from September 1st, 2014.</p>

<p>Group Web Page: http://www.lcqb.upmc.fr/AnalGenom/home.html</p>

<p>Ref. E-Mail: Alessandra Carbone alessandra.carbone@lip6.fr</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19187/srbioinformatics-analyst-ngs-at-ocimum-biosolution</guid>
  <pubDate>Sat, 15 Nov 2014 04:46:10 -0600</pubDate>
  <link></link>
  <title><![CDATA[Sr.Bioinformatics Analyst (NGS) at Ocimum Biosolution]]></title>
  <description><![CDATA[
<p>“Ocimum Biosolution” is a comprehensive Integrated Life Science Informatics solutions provider with service offerings that span Sample and Data Management (LIMS, Biologics Data Management), Genomics Data Analysis Services such as Gene Expression, Genotyping, and Next Gen Sequencing, Bioinformatics and Genomics Databases (BioExpress®, ToxExpress®) and Bio-IT consulting services.</p>

<p>Experience Required: 3-5 years of experience</p>

<p>No of Positions : Multiple</p>

<p>Qualifications: Candidates with minimum qualification as M.Sc Bioinformatics with 3-5  years of experience in Life sciences R&amp;D or Pharma Industry.</p>

<p>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.</p>

<p>2. Experience in application development or must have expertise in programming using either of Perl/Python.</p>

<p>3.  Experience in statistical programming using R/Bioconductor/Matlab.</p>

<p>4. Strong concept in statistical and mathematical modelling.</p>

<p>5.  Experience in designing and developing the bioinformatics pipeline.</p>

<p>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.</p>

<p>7. Knowledge in WGS ,WES, Targeted re-sequencing,GWAS and population genomics will be preferred.</p>

<p>8. Must have experience working on opensource software/Framework and commercial software for NGS data analysis and reporting.</p>

<p>9. Should be aware of handling big data and guiding team members on multiple projects simultaneously.</p>

<p>10. Should have experience coordinating with different groups of clinical research scientist for various project requirements.</p>

<p>11. Ability to work as team as well as independently with minimal support.</p>

<p>More at http://www.ocimumbio.com/careers1/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24298/staff-scientists-at-national-institute-of-plant-genome-research-new-delhi</guid>
  <pubDate>Fri, 04 Sep 2015 22:06:59 -0500</pubDate>
  <link></link>
  <title><![CDATA[Staff Scientists at National Institute of Plant Genome Research, New Delhi]]></title>
  <description><![CDATA[
<p>National Institute of Plant Genome Research, New Delhi is an Autonomous Research Institution funded by Department of Biotechnology, Ministry of Science &amp; Technology, Govt. of India, to pursue research on various aspects of plant genomics. The Institute is also in the process of establishing a NIPGR Translational Centre at Biotech Science Cluster, NCR, Faridabad. NIPGR invites applications from Indian Citizens for filling up the vacant posts on Direct Recruitment basis, as detailed below. The posts are temporary but likely to continue.</p>

<p>Staff Scientists</p>

<p>Specialization: Applicant should have a Ph.D. with excellent academic credentials along with the track record of scientific productivity evidenced by publications/patents/products in the frontier areas of Plant Biology such as, Computational Biology, Genome Analysis and Molecular Mapping, Molecular Mechanism of Abiotic Stress Responses, Nutritional Genomics, Plant Development and Architecture, Plant Immunity, Molecular Breeding, Transgenics for crop improvement and other emerging areas based on plant genomics.</p>

<p>Remuneration: The length of experience and scientific accomplishments/quality of scientific productivity record will be major factors in deciding the level of appointment as Staff Scientist as well as starting salary in the Pay Bands of Rs 15,600-39,100 (with grade pay of  5400), and Rs 37,400-67,000 (with grade pay of  8,700 and  8,900) plus usual allowances admissible to the Central Government employees. However, NIPGR reserves the right to select candidates in the lower grade against the foregoing posts depending upon the qualifications and experience of the candidate. Reservation of posts shall be as per Govt. of India norms. Five posts (SC-2, ST-1, OBC-2) in the Pay Band of Rs 15,600-39,100 with Grade Pay of  Rs 5400, are reserved.</p>

<p>More at http://www.nipgr.res.in/careers/vacancies_latest.php#</p>

<p>Apply online at http://www.nipgr.res.in/nipgr_recu/nipgr_recu.php</p>

<p>Form http://www.nipgr.res.in/files/careers/Application_Performa_2015.doc</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27113/picard</guid>
	<pubDate>Fri, 29 Apr 2016 08:21:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27113/picard</link>
	<title><![CDATA[Picard]]></title>
	<description><![CDATA[<p>Picard is a set of command line tools for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF. These file formats are defined in the <a href="http://samtools.github.io/hts-specs/">Hts-specs</a> repository. See especially the <a href="http://samtools.github.io/hts-specs/SAMv1.pdf">SAM specification</a> and the <a href="http://samtools.github.io/hts-specs/VCFv4.3.pdf">VCF specification</a>.</p>
<p>Note that the information on this page is targeted at end-users. For developers, the source code, building instructions and implementation/development resources are available on <a href="https://github.com/broadinstitute/picard">GitHub</a>.</p>
<p>The Picard toolkit is open-source under the <a href="https://tldrlegal.com/license/mit-license">MIT license</a> and free for all uses.</p>
<p>Enjoy!</p><p>Address of the bookmark: <a href="http://broadinstitute.github.io/picard/" rel="nofollow">http://broadinstitute.github.io/picard/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26828/bioinfolab</guid>
  <pubDate>Fri, 25 Mar 2016 11:05:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[BioinfoLab]]></title>
  <description><![CDATA[
<p>Laboratory of Statistics and Computational tools for Bioinformatics</p>

<p>The Laboratory of Statistics and Computational tools for Bioinformatics (BioinfoLab) is hosted at the Istituto per le Applicazioni del Calcolo "Mauro Picone" - CNR . The laboratory has been officially opened in 2012 with the support of Programma Operativo Nazionale "Ricerca e Competitività" 2007-2013 (PON "R&amp;C"), and it incorporates several expertise and research activities started since 2007, and supported by several CNR projects. Main interest of BioinfoLab is to develop novel statistical methods and computational tools for the analysis of high dimensional data arising from "Multi-omics" applications. In particular, current activities involve the analysis of ChIP-seq and RNA-seq experiments. </p>

<p>More at http://bioinfo.na.iac.cnr.it/BioinfoLab/index.html</p>
]]></description>
</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>
<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/27076/ale-a-generic-assembly-likelihood-evaluation-framework-for-assessing-the-accuracy-of-genome-and-metagenome-assemblies</guid>
	<pubDate>Tue, 26 Apr 2016 03:38:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27076/ale-a-generic-assembly-likelihood-evaluation-framework-for-assessing-the-accuracy-of-genome-and-metagenome-assemblies</link>
	<title><![CDATA[ALE: a Generic Assembly Likelihood Evaluation Framework for Assessing the Accuracy of Genome and Metagenome Assemblies]]></title>
	<description><![CDATA[<p>Assembly Likelihood Evaluation (ALE) framework that overcomes these limitations, systematically evaluating the accuracy of an assembly in a reference-independent manner using rigorous statistical methods. This framework is comprehensive, and integrates read quality, mate pair orientation and insert length (for paired-end reads), sequencing coverage, read alignment and k-mer frequency. ALE pinpoints synthetic errors in both single and metagenomic assemblies, including single-base errors, insertions/deletions, genome rearrangements and chimeric assemblies presented in metagenomes. At the genome level with real-world data, ALE identifies three large misassemblies from the Spirochaeta smaragdinae finished genome, which were all independently validated by Pacific Biosciences sequencing. At the single-base level with Illumina data, ALE recovers 215 of 222 (97%) single nucleotide variants in a training set from a GC-rich Rhodobacter sphaeroides genome. Using real Pacific Biosciences data, ALE identifies 12 of 12 synthetic errors in a Lambda Phage genome, surpassing even Pacific Biosciences' own variant caller, EviCons. In summary, the ALE framework provides a comprehensive, reference-independent and statistically rigorous measure of single genome and metagenome assembly accuracy, which can be used to identify misassemblies or to optimize the assembly process.</p>
<p>More at&nbsp;http://www.ncbi.nlm.nih.gov/pubmed/23303509</p><p>Address of the bookmark: <a href="http://sc932.github.io/ALE/about.html" rel="nofollow">http://sc932.github.io/ALE/about.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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