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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29272?offset=1150</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10773/bioinformatics-jrfsrf-position-at-national-research-centre-on-plant-biotechnology</guid>
  <pubDate>Sun, 11 May 2014 22:29:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/SRF position at NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY]]></title>
  <description><![CDATA[
<p>NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY<br />LBS, CENTRE, PUSA CAMPUS, IARI NEW DELHI<br />NEW DELHI – 110 012</p>

<p>WALK- IN –INTERVIEWS</p>

<p>Eligible candidates may appear in Walk-in-Interview on May 23, 2014 at 10 AM for the posts of Research Associates &amp; Senior Research Fellows (SRF) in the following DST/DBT/ICAR funded projects.</p>

<p>1 NPTC Project on Bioinformatics and Comparative Genomics</p>

<p>Research Associate (One)</p>

<p>Rs. 24000/- + 30% HRA for masters degree holder with more than 4 years experience</p>

<p>Essential: Ph D in Plant Molecular Biology &amp; Biotechnology/Genetics 0r Candidates who have already submitted their Ph D thesis in above subjects</p>

<p>Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.</p>

<p>Senior Research Fellow ( UGCCSIR/ DBT/ ICAR Net qualified only): (One)</p>

<p>Rs. 16000/- + 30% HRA and Rs. 18000+30 HRA from 3rd year onwards</p>

<p>Essential:</p>

<p>1. ICAR/ UGCCSIR/DBT Net qualified only</p>

<p>2. M. Sc. (with thesis) in Biotechnology, Life Sciences, Biosciences/ Bioinformatics, Genetics/ Plant Pathology with experience in molecular biology.</p>

<p>Or M.Sc with more than 3 years research experiences</p>

<p>3. B.Sc. Agriculture or Biology</p>

<p>Desirable:<br />1. M. Sc. with thesis<br />2. Experience in molecular biology, plant tissue culture<br />3. Bioinformatics knowledge is important</p>

<p>2 DST JC Bose National Fellowship</p>

<p>Research Associate (Bioinformatics) : One</p>

<p>Rs.22000/- + 30% HRA for 1 &amp; 2nd Yr., Rs. 23000+ 30% HRA for 3rd year and Rs. 24000+30% HRA for 4th &amp;5th yr</p>

<p>Essential: M Ph D in Plant Molecular Biology &amp; Biotechnology/Genetics</p>

<p>Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.</p>

<p>Age limit: Max.35 years (Age relaxation of 5 years for SC/ST &amp; women and 3 years for OBC)</p>

<p>The posts are purely temporary in nature and are co-terminus with the project. Initially the offer will be made for one year only and may be further extendable based on performance of the candidate. The interview will be held on May 23 , 2014 at 10:00 AM at NRCPB, LBS Building, Pusa Campus, IARI, New Delhi- 110012. The candidates must bring four copies of biodata (in the prescribed proforma), original certificates, attested photocopies of each of the certificates and an attested copy of recent passport size photograph. No. TA/DA would be given for the appearance in interview. Only the candidates having essential qualification would be entertained for the interviews. Short-listing of candidates based on academic merit and experience will be done in case of large number of applicants.</p>

<p>Advertisement: http://www.nrcpb.org/sites/default/files/Advertisement%20for%20RA%20and%20SRF%20Position.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</guid>
	<pubDate>Wed, 29 Nov 2017 07:40:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</link>
	<title><![CDATA[Ribbon: Visualizing complex genome alignments and structural variation:]]></title>
	<description><![CDATA[<p>Ribbon can be used for long reads, short reads, paired-end reads, and assembly/genome alignments. Instructions for each data format are available by clicking on "instructions" in each tab on the right.</p>
<p>Local installation:</p>
<p>You can install Ribbon locally from Github by following the instructions here:&nbsp;<a href="https://github.com/MariaNattestad/ribbon" target="_blank">https://github.com/MariaNattestad/Ribbon</a></p><p>Address of the bookmark: <a href="http://genomeribbon.com/" rel="nofollow">http://genomeribbon.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/12943/a-history-of-bioinformatics-in-the-year-2039</guid>
	<pubDate>Wed, 23 Jul 2014 06:37:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/12943/a-history-of-bioinformatics-in-the-year-2039</link>
	<title><![CDATA[A History of Bioinformatics (in the Year 2039)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/uwsjwMO-TEA" frameborder="0" allowfullscreen></iframe><p>C. Titus Brown http://video.open-bio.org/video/1/a-history-of-bioinformatics-in-the-year-2039</p>]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</guid>
	<pubDate>Fri, 08 Dec 2017 16:26:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</link>
	<title><![CDATA[jobTree based python wrapper to run the genome simulation tool suite Evolver]]></title>
	<description><![CDATA[<p><span>evolverSimControl</span><span>&nbsp;(</span><span>eSC</span><span>) can be used to simulate multi-chromosome genome evolution on an arbitrary phylogeny (</span><a href="http://evolution.genetics.washington.edu/phylip/newicktree.html">Newick format</a><span>). In addition to simply running evolver,&nbsp;</span><span>eSC</span><span>&nbsp;also automatically creates statistical summaries of the simulation as it runs including text and image files. Also included are convenience scripts to: check on a running simulation and see detailed status and logging information; extract fasta sequence files from the leaf nodes of a completed simulation; extract pairwise multiple alignment files (</span><a href="http://genome.ucsc.edu/FAQ/FAQformat.html#format5">.maf</a><span>) from leaf and branch nodes from a completed simulation and with the help of&nbsp;</span><a href="https://github.com/dentearl/mafTools/">mafJoin</a><span>, join them together into a single maf covering the entire simulation.</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/evolverSimControl" rel="nofollow">https://github.com/dentearl/evolverSimControl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/11144/scientists-map-17294-proteins-produced-in-human-body</guid>
	<pubDate>Thu, 29 May 2014 01:57:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/11144/scientists-map-17294-proteins-produced-in-human-body</link>
	<title><![CDATA[Scientists map 17,294 proteins produced in human body]]></title>
	<description><![CDATA[<p>Indian scientists missed the genomic profiling bus, but they've more than made up for it by creating the first human proteome map which is an extension of the genomic study. Till now, here is no direct equivalent for the human proteome. But recently two groups present mass spectrometry-based analysis of human tissues, body fluids and cells mapping the large majority of the human proteome.</p><p>The Indian scientists working in Bangalore, along with their American counterparts, have mapped more than 17,000 proteins in 30 organs of the human body. Just like the human genome was sequenced around the turn of the millennium, this is an equivalent mapping of the human proteome.<br /><br />The researcher estimated there are around 20,500 proteins in the human body. These scientists have profiled around 17,294, which account for around 84% of the total proteins. Apart from this, the team also traced around 2,500 of 3,000 proteins that had been categorised as "missing proteins".</p><p>The work, done by group of Indian scientists, and Johns Hopkins University, published in the renowned journal Nature ( http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html ). Of the 72 people who worked on the project, 46 are Indians.</p><p>Reference:</p><p>http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html</p><p>http://www.proteinatlas.org/ -The antibody-based Human Protein Atlas programme</p><p>http://www.humanproteomemap.org/ -Proteogenomic analysis by identifying translated proteins from annotated pseudogenes, non-coding RNAs and untranslated regions.</p><p>https://www.proteomicsdb.org/ -Assembled protein evidence for 18,097 genes in ProteomicsDB</p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34620/mash-fast-genome-and-metagenome-distance-estimation-using-minhash</guid>
	<pubDate>Tue, 12 Dec 2017 17:30:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34620/mash-fast-genome-and-metagenome-distance-estimation-using-minhash</link>
	<title><![CDATA[Mash: fast genome and metagenome distance estimation using MinHash]]></title>
	<description><![CDATA[<p>Mash is normally distributed as a dependency-free binary for Linux or OSX (see&nbsp;<a href="https://github.com/marbl/Mash/releases">https://github.com/marbl/Mash/releases</a>). This source distribution is intended for other operating systems or for development. Mash requires c++11 to build, which is available in and GCC &gt;= 4.8 and OSX &gt;= 10.7.</p>
<p>See&nbsp;<a href="http://mash.readthedocs.org/">http://mash.readthedocs.org</a>&nbsp;for more information.</p><p>Address of the bookmark: <a href="https://github.com/marbl/Mash/releases" rel="nofollow">https://github.com/marbl/Mash/releases</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35131/giggle-a-search-engine-for-large-scale-integrated-genome-analysis</guid>
	<pubDate>Wed, 10 Jan 2018 03:10:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35131/giggle-a-search-engine-for-large-scale-integrated-genome-analysis</link>
	<title><![CDATA[GIGGLE: a search engine for large-scale integrated genome analysis]]></title>
	<description><![CDATA[<p><span>GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (</span><a href="https://github.com/ryanlayer/giggle">https://github.com/ryanlayer/giggle</a><span>) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.</span></p>
<p>https://www.nature.com/articles/nmeth.4556</p><p>Address of the bookmark: <a href="https://github.com/ryanlayer/giggle" rel="nofollow">https://github.com/ryanlayer/giggle</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</guid>
	<pubDate>Sun, 01 Jun 2014 23:38:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</link>
	<title><![CDATA[Genomics and Personalized Medicine]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/pgHAXCMMcro" frameborder="0" allowfullscreen></iframe>(October 20, 2009) Michael Snyder, Professor of Genetics and Chair of the Department of Genetics at Stanford, discusses advances in gene sequencing, the impact of genomics on medicine, the potential for personalized medicine. and efforts at Stanford to further study these issues.

Stanford Mini Med School is a series arranged and directed by Stanford's School of Medicine, and presented by the Stanford Continuing Studies program. Featuring more than thirty distinguished, faculty, scientists and physicians from Stanford's medical school, the series offers students a dynamic introduction to the world of human biology, health and disease, and the groundbreaking changes taking place in medical research and health care.

Stanford University
http://www.stanford.edu

Stanford University School of Medicine
http://med.stanford.edu

Stanford Continuing Studies
http://continuingstudies.stanford.edu

Stanford University Channel on YouTube:
http://www.youtube.com/stanford]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35432/mummer4-a-fast-and-versatile-genome-alignment-system</guid>
	<pubDate>Sat, 03 Feb 2018 04:59:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35432/mummer4-a-fast-and-versatile-genome-alignment-system</link>
	<title><![CDATA[MUMmer4: A fast and versatile genome alignment system]]></title>
	<description><![CDATA[<p><span>MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the&nbsp;</span><span>nucmer</span><span>&nbsp;program in MUMmer4 is easily able to handle alignments of large genomes;&nbsp;</span></p><p>Address of the bookmark: <a href="https://mummer4.github.io/" rel="nofollow">https://mummer4.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11434/adhoc-bioinformatics-faculty-position-nit</guid>
  <pubDate>Tue, 03 Jun 2014 16:19:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Adhoc Bioinformatics Faculty Position @ NIT]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF TECHNOLOGY, DEPARTMENT OF BIOTECHNOLOGY, WARANGAL – 506 021, Andhra Pradesh</p>

<p>No.NITW/BT/2014/adhoc</p>

<p>APPLICATIONS ARE INVITED FOR THE APPOINTMENT OF ADHOC FACULTY ON CONTRACT BASIS IN THE DEAPARTMENT OF BIOTECHNOLOGY</p>

<p>Period of Contract: Initially the appointment is for one semester i.e., from July 2014 up to December 2014 only.</p>

<p>Essential Qualifications:</p>

<p>i) B. Tech or equivalent in Biotechnology/ Industrial Biotechnology/ Biochemical Engineering / Chemical Engg. Or M. Sc in Microbiology/ Botany/ Zoology/ Biochemistry/Biotechnology and ii) M. Tech or equivalent in Biotechnology/Industrial Biotechnology/Bioinformatics</p>

<p>Or</p>

<p>Integrated M. Tech in Biotechnology/Industrial Biotechnology/ Bioinformatics</p>

<p>Candidates must possess First class (60% aggregate marks or 6.5 CGPA) at B. Tech/ M. Sc and M. Tech.</p>

<p>Desirable: Ph. D Pay Package: All selected candidates shall be eligible for a consolidated pay of Rs.30, 000/- per month. Candidates with Ph. D shall be eligible for an additional amount of Rs.5, 000/- per month.</p>

<p>How to apply : Applications on plain paper with attested photocopies of certificate and bio data along with justification for eligibility should reach to the Head, Department of Biotechnology, National Institute of Technology, Warangal AP 506004 in the form of soft or hard copy on or before 21st June 2014 email : biotech_hod@nitw.ac.in</p>

<p>Intimation: No separate call letters will be sent to the candidates. All the eligible candidates will be notified in the institute web site on 23rd June 2014. All the eligible candidates are requested to report for the interview to the Head, Department of Biotechnology at 9:00 AM on 27th June 2014</p>

<p>Joining: Selected candidates will be informed and they are expected to join immediately.</p>

<p>Advertisement:</p>

<p>http://www.nitw.ac.in/nitw/announcements/2014/Bio-Adhoc%20Advt.%20May-2014.pdf</p>
]]></description>
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