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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37993?offset=170</link>
	<atom:link href="https://bioinformaticsonline.com/related/37993?offset=170" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</guid>
	<pubDate>Tue, 17 Sep 2024 02:28:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</link>
	<title><![CDATA[Figeno: Tool for plotting sequencing data along genomic coordinates.]]></title>
	<description><![CDATA[<p><span>Tool for plotting sequencing data along genomic coordinates.</span></p>
<div>
<pre><code>FIGENO is a
  FIGure
    GENerator
for GENOmics</code></pre>
</div>
<p dir="auto">With figeno, you can plot various types of sequencing data along genomic coordinates. Video overview:&nbsp;<a href="https://www.youtube.com/watch?v=h1cBeXoSYTA">https://www.youtube.com/watch?v=h1cBeXoSYTA</a>.</p>
<p dir="auto"><a href="https://github.com/CompEpigen/figeno/blob/main/docs/content/images/figeno.png" target="_blank"><img src="https://github.com/CompEpigen/figeno/raw/main/docs/content/images/figeno.png" alt="figeno" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/CompEpigen/figeno" rel="nofollow">https://github.com/CompEpigen/figeno</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/33869/import-r-data</guid>
	<pubDate>Wed, 12 Jul 2017 08:30:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/33869/import-r-data</link>
	<title><![CDATA[Import R Data]]></title>
	<description><![CDATA[<p>It is often necessary to import sample textbook data into R before you start working on your homework.</p><div id="node-69"><div><p><strong>Excel File</strong></p><p>Quite frequently, the sample data is in&nbsp;<span>Excel&nbsp;</span>format, and needs to be imported into R prior to use. For this, we can use the function&nbsp;<span>read.xls&nbsp;</span>from the&nbsp;<span>gdata&nbsp;</span>package. It reads from an Excel spreadsheet and returns a&nbsp;<a href="http://www.r-tutor.com/r-introduction/data-frame">data frame</a>. The following shows how to load an Excel spreadsheet named&nbsp;<span>"mydata.xls"</span>. This method requires Perl runtime to be present in the system.</p><blockquote><div id="listing-68"><span><a></a></span>&gt;&nbsp;library(gdata)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;load&nbsp;gdata&nbsp;package&nbsp;<br /><span><a></a></span>&gt;&nbsp;help(read.xls)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;documentation&nbsp;<br /><span><a></a></span>&gt;&nbsp;mydata&nbsp;=&nbsp;read.xls("mydata.xls")&nbsp;&nbsp;#&nbsp;read&nbsp;from&nbsp;first&nbsp;sheet</div></blockquote><p>Alternatively, we can use the function&nbsp;<span>loadWorkbook&nbsp;</span>from the&nbsp;<span>XLConnect&nbsp;</span>package to read the entire workbook, and then load the worksheets with&nbsp;<span>readWorksheet</span>. The&nbsp;<span>XLConnect&nbsp;</span>package requires Java to be pre-installed.</p><blockquote><div id="listing-69"><span><a></a></span>&gt;&nbsp;library(XLConnect)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;load&nbsp;XLConnect&nbsp;package&nbsp;<br /><span><a></a></span>&gt;&nbsp;wk&nbsp;=&nbsp;loadWorkbook("mydata.xls")&nbsp;<br /><span><a></a></span>&gt;&nbsp;df&nbsp;=&nbsp;readWorksheet(wk,&nbsp;sheet="Sheet1")</div></blockquote><p>&nbsp;</p><h4><a></a>Minitab File</h4><p>If the data file is in&nbsp;<span>Minitab Portable Worksheet&nbsp;</span>format, it can be opened with the function&nbsp;<span>read.mtp&nbsp;</span>from the&nbsp;<span>foreign&nbsp;</span>package. It returns a&nbsp;<a href="http://www.r-tutor.com/r-introduction/list">list</a>&nbsp;of components in the Minitab worksheet.</p><blockquote><div id="listing-70"><span><a></a></span>&gt;&nbsp;library(foreign)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;load&nbsp;the&nbsp;foreign&nbsp;package&nbsp;<br /><span><a></a></span>&gt;&nbsp;help(read.mtp)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;documentation&nbsp;<br /><span><a></a></span>&gt;&nbsp;mydata&nbsp;=&nbsp;read.mtp("mydata.mtp")&nbsp;&nbsp;#&nbsp;read&nbsp;from&nbsp;.mtp&nbsp;file</div></blockquote><p>&nbsp;</p><h4><a></a>SPSS File</h4><p>For the data files in&nbsp;<span>SPSS&nbsp;</span>format, it can be opened with the function&nbsp;<span>read.spss&nbsp;</span>also from the&nbsp;<span>foreign&nbsp;</span>package. There is a&nbsp;<span>"to.data.frame"&nbsp;</span>option for choosing whether a data frame is to be returned. By default, it returns a list of components instead.</p><blockquote><div id="listing-71"><span><a></a></span>&gt;&nbsp;library(foreign)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;load&nbsp;the&nbsp;foreign&nbsp;package&nbsp;<br /><span><a></a></span>&gt;&nbsp;help(read.spss)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;documentation&nbsp;<br /><span><a></a></span>&gt;&nbsp;mydata&nbsp;=&nbsp;read.spss("myfile",&nbsp;to.data.frame=TRUE)</div></blockquote><p>&nbsp;</p><h4><a></a>Table File</h4><p>A data table can resides in a text file. The cells inside the table are separated by blank characters. Here is an example of a table with 4 rows and 3 columns.</p><blockquote><div id="listing-72"><span><a></a></span>100&nbsp;&nbsp;&nbsp;a1&nbsp;&nbsp;&nbsp;b1&nbsp;<br /><span><a></a></span>200&nbsp;&nbsp;&nbsp;a2&nbsp;&nbsp;&nbsp;b2&nbsp;<br /><span><a></a></span>300&nbsp;&nbsp;&nbsp;a3&nbsp;&nbsp;&nbsp;b3&nbsp;<br /><span><a></a></span>400&nbsp;&nbsp;&nbsp;a4&nbsp;&nbsp;&nbsp;b4</div></blockquote><p>Now copy and paste the table above in a file named&nbsp;<span>"mydata.txt"&nbsp;</span>with a text editor. Then load the data into the workspace with the function&nbsp;<span>read.table</span>.</p><blockquote><div id="listing-73"><span><a></a></span>&gt;&nbsp;mydata&nbsp;=&nbsp;read.table("mydata.txt")&nbsp;&nbsp;#&nbsp;read&nbsp;text&nbsp;file&nbsp;<br /><span><a></a></span>&gt;&nbsp;mydata&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;print&nbsp;data&nbsp;frame&nbsp;<br /><span><a></a></span>&nbsp;&nbsp;&nbsp;V1&nbsp;V2&nbsp;V3&nbsp;<br /><span><a></a></span>1&nbsp;100&nbsp;a1&nbsp;b1&nbsp;<br /><span><a></a></span>2&nbsp;200&nbsp;a2&nbsp;b2&nbsp;<br /><span><a></a></span>3&nbsp;300&nbsp;a3&nbsp;b3&nbsp;<br /><span><a></a></span>4&nbsp;400&nbsp;a4&nbsp;b4</div></blockquote><p>For further detail of the function&nbsp;<span>read.table</span>, please consult the R documentation.</p><blockquote><div id="listing-74"><span><a></a></span>&gt;&nbsp;help(read.table)</div></blockquote><p>&nbsp;</p><h4><a></a>CSV File</h4><p>The sample data can also be in&nbsp;<span>comma separated values&nbsp;</span>(CSV) format. Each cell inside such data file is separated by a special character, which usually is a comma, although other characters can be used as well.</p><p>The first row of the data file should contain the column names instead of the actual data. Here is a sample of the expected format.</p><blockquote><div id="listing-75"><span><a></a></span>Col1,Col2,Col3&nbsp;<br /><span><a></a></span>100,a1,b1&nbsp;<br /><span><a></a></span>200,a2,b2&nbsp;<br /><span><a></a></span>300,a3,b3</div></blockquote><p>After we copy and paste the data above in a file named&nbsp;<span>"mydata.csv"&nbsp;</span>with a text editor, we can read the data with the function&nbsp;<span>read.csv</span>.</p><blockquote><div id="listing-76"><span><a></a></span>&gt;&nbsp;mydata&nbsp;=&nbsp;read.csv("mydata.csv")&nbsp;&nbsp;#&nbsp;read&nbsp;csv&nbsp;file&nbsp;<br /><span><a></a></span>&gt;&nbsp;mydata&nbsp;<br /><span><a></a></span>&nbsp;&nbsp;Col1&nbsp;Col2&nbsp;Col3&nbsp;<br /><span><a></a></span>1&nbsp;&nbsp;100&nbsp;&nbsp;&nbsp;a1&nbsp;&nbsp;&nbsp;b1&nbsp;<br /><span><a></a></span>2&nbsp;&nbsp;200&nbsp;&nbsp;&nbsp;a2&nbsp;&nbsp;&nbsp;b2&nbsp;<br /><span><a></a></span>3&nbsp;&nbsp;300&nbsp;&nbsp;&nbsp;a3&nbsp;&nbsp;&nbsp;b3</div></blockquote><p>In various European locales, as the comma character serves as the decimal point, the function&nbsp;<span>read.csv2&nbsp;</span>should be used instead. For further detail of the&nbsp;<span>read.csv&nbsp;</span>and&nbsp;<span>read.csv2&nbsp;</span>functions, please consult the R documentation.</p><blockquote><div id="listing-77"><span><a></a></span>&gt;&nbsp;help(read.csv)</div></blockquote><p>&nbsp;</p><h4><a></a>Working Directory</h4><p>Finally, the code samples above assume the data files are located in the R&nbsp;<span>working</span>&nbsp;<span>directory</span>, which can be found with the function&nbsp;<span>getwd</span>.</p><blockquote><div id="listing-78"><span><a></a></span>&gt;&nbsp;getwd()&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;get&nbsp;current&nbsp;working&nbsp;directory</div></blockquote><p>You can select a different working directory with the function&nbsp;<span>setwd()</span>, and thus avoid entering the full path of the data files.</p><blockquote><div id="listing-79"><span><a></a></span>&gt;&nbsp;setwd("")&nbsp;&nbsp;&nbsp;#&nbsp;set&nbsp;working&nbsp;directory</div></blockquote><p>Note that the forward slash should be used as the path separator even on Windows platform.</p><blockquote><div id="listing-80"><span><a></a></span>&gt;&nbsp;setwd("C:/MyDoc")</div></blockquote></div></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</guid>
	<pubDate>Tue, 27 Nov 2018 04:43:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</link>
	<title><![CDATA[lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data]]></title>
	<description><![CDATA[<p><span>lordFAST is a sensitive tool for mapping long reads with high error rates. lordFAST is specially designed for aligning reads from PacBio sequencing technology but provides the user the ability to change alignment parameters depending on the reads and application.</span></p>
<p>lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/lordfast" rel="nofollow">https://github.com/vpc-ccg/lordfast</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40613/genome-in-a-bottle-giab-consortium</guid>
	<pubDate>Sat, 25 Jan 2020 13:50:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40613/genome-in-a-bottle-giab-consortium</link>
	<title><![CDATA[Genome in a Bottle (GIAB) Consortium]]></title>
	<description><![CDATA[<p><span>The</span><a href="http://www.genomeinabottle.org/"> Genome in a Bottle (GIAB) Consortium</a><span> is a public-private-academic consortium hosted by </span><a href="http://www.nist.gov/" target="_blank">NIST</a><span> to develop the technical infrastructure (reference standards, reference methods, and reference data) to enable translation of whole human genome sequencing to clinical practice. </span></p>
<p><span><a href="https://www.nist.gov/news-events/news/2016/09/nist-releases-new-family-standardized-genomes">https://www.nist.gov/news-events/news/2016/09/nist-releases-new-family-standardized-genomes</a></span></p><p>Address of the bookmark: <a href="https://jimb.stanford.edu/giab/" rel="nofollow">https://jimb.stanford.edu/giab/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42581/autogluon-automl-for-text-image-and-tabular-data</guid>
	<pubDate>Thu, 07 Jan 2021 05:33:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42581/autogluon-automl-for-text-image-and-tabular-data</link>
	<title><![CDATA[AutoGluon: AutoML for Text, Image, and Tabular Data]]></title>
	<description><![CDATA[<p><span>AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on text, image, and tabular data.</span></p><p>Address of the bookmark: <a href="https://github.com/awslabs/autogluon" rel="nofollow">https://github.com/awslabs/autogluon</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44742/nasa-open-science-data-repository</guid>
	<pubDate>Wed, 18 Dec 2024 11:54:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44742/nasa-open-science-data-repository</link>
	<title><![CDATA[NASA Open Science Data Repository]]></title>
	<description><![CDATA[<p><span>The NASA Open Science Data Repository (OSDR) enables access to space-related data from experiments and missions that investigate biological and health responses of terrestrial life to spaceflight. The goal of OSDR is to enable multi-modal and multi-hierarchical fundamental space life science data be reused toward basic science, applied science, and operational outcomes for space exploration and knowledge discovery. These data include &lsquo;omics, phenotypic, physiological, behavioral, hardware, environmental telemetry; raw, processed; tabular, text, code, bioimaging, and video.</span></p>
<p><span>https://www.nasa.gov/reference/osdr-data-processing/</span></p><p>Address of the bookmark: <a href="https://www.nasa.gov/osdr/" rel="nofollow">https://www.nasa.gov/osdr/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34914/ra-assembler-a-de-novo-dna-assembler-for-third-generation-sequencing-data</guid>
	<pubDate>Wed, 27 Dec 2017 20:36:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34914/ra-assembler-a-de-novo-dna-assembler-for-third-generation-sequencing-data</link>
	<title><![CDATA[Ra assembler - a de novo DNA assembler for third generation sequencing data]]></title>
	<description><![CDATA[<p>Integration of the Ra assembler - a de novo DNA assembler for third generation sequencing data developed on Faculty of Electrical Engineering and Computing (FER), Ruder Boskovic Institute (RBI) and Genome Institute of Singapore (GIS).</p>
<p>Ra is in development since 2014 in the form of several separate components that used to be run individually.<br>This project aims to ease the usage of Ra by integrating it into a complete de novo assembly tool.</p>
<p>Unlike other state-of-the-art assemblers,&nbsp;<span>Ra does not have an error correction step.</span>&nbsp;Instead, it relies on detecting overlaps using a very sensitive and specific overlapper ("graphmap -w owler",&nbsp;<a href="https://github.com/isovic/graphmap">https://github.com/isovic/graphmap</a>) and constructing and reducing an overlap graph (Ra layout,&nbsp;<a href="https://github.com/mariokostelac/ra">https://github.com/mariokostelac/ra</a>).</p><p>Address of the bookmark: <a href="https://github.com/mariokostelac/ra-integrate/" rel="nofollow">https://github.com/mariokostelac/ra-integrate/</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/843/structural-polymorphism-analysis-from-ngs-data</guid>
  <pubDate>Sat, 13 Jul 2013 17:12:47 -0500</pubDate>
  <link></link>
  <title><![CDATA[Structural polymorphism analysis from NGS data]]></title>
  <description><![CDATA[
<p>The LabEx BASC (Biodiversity, Agroecosystems, Society, Climate), a network of 13 laboratories of the Paris-Saclay Scientific Cluster, is seeking a bioinformatician to analyze Next Generation Sequencing (NGS) data analysis. In the context of a flagship project aiming at understanding and improving the adaptive capacity of agroecosystems it will be critical to establish a link between sequence variation, functional variation, gene/protein expression and phenotypic adaptation.</p>

<p>The successful candidate will be in charge of the detection of polymorphisms including structural variants, of the comparison of multiple and diverse genomes of a same species and of the construction of pan- and core-genomes. These challenging tasks will require bioinformatics developments and implementation of methods for accommodating the high level of repetitiveness of complex genomes. The tools will be integrated into pipelines and made available to end-users through the Galaxy platform. The bioinformatician will therefore also have to provide researchers with advices on their experimental designs in order to ensure compliance of produced datasets with pipelines requirements. He/she will be hosted by a bioinformatics/informatics team (7 people) (http://moulon.inra.fr/index.php/fr/equipestransversales/atelier-de-bioinformatique) which has computational facilities and expertise in NGS data analysis, and will benefit as well from national and international collaborative networks (Aplibio http://www.renabi.fr/platforms/aplibio/, Transplant http://transplantdb.eu, AMAIZING http://www.amaizing.fr/).</p>

<p>The position requires a doctoral degree (PhD) in bioinformatics with strong expertise in script writing (Python/Perl) and pipeline development. </p>

<p>Applicants should send a CV and the names of 2 referees willing to provide a letter of recommendation to joets@moulon.inra.fr.</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/2054/postdoc-positions-mammalian-transcriptome-evolution-at-sib</guid>
  <pubDate>Mon, 12 Aug 2013 19:58:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc Positions - Mammalian Transcriptome Evolution at SIB]]></title>
  <description><![CDATA[
<p>BIOINFORMATICS POSTDOC IN FUNCTIONAL EVOLUTIONARY GENOMICS</p>

<p>Center for Integrative Genomics, University of Lausanne, Switzerland</p>

<p>Two postdoctoral positions (2 years with possible extensions up to 5 years) are available immediately in the evolutionary genomics group of Henrik Kaessmann.</p>

<p>We are seeking highly qualified and enthusiastic applicants with strong skills in computational biology/bioinformatics, preferably also with experience in data mining and comparative or evolutionary genome analysis.</p>

<p>We have been interested in a range of topics related to the functional evolution of genomes from primates (e.g., the emergence of new genes and their functions) and other mammals (e.g., the origin and evolution of mammalian sex chromosomes). In the framework of a recently launched series of projects, a large amount of transcriptome and genome (e.g., epigenome) data are being produced by the wet lab unit of the group using next generation sequencing technologies for a unique collection of tissues from representative mammals and outgroup species (e.g., birds). Topics of current projects based on these data include the origins and/or evolution of protein-coding genes, alternative splicing, microRNAs, long noncoding RNAs, and dosage compensation.</p>

<p>The postdoctoral fellow will perform integrated evolutionary/bioinformatics analyses based on data produced in the lab and available genomic data. The specific project will be developed together with the candidate.</p>

<p>The language of the institute is English, and its members form an international group that is rapidly expanding. The institute is located in Lausanne, a beautiful city at Lake Geneva.</p>

<p>For more information on the group and our institute more generally, please refer to our website: http://www.unil.ch/cig/page7858_en.html</p>

<p>Please submit a CV, statement of research interest, and names of three references to: Henrik Kaessmann (Henrik.Kaessmann@unil.ch).</p>

<p>Webpage : http://www.unil.ch/cig/page7858.html</p>
]]></description>
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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>
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