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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/2759?offset=120</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30658/srf-bioinformatics-at-jnu</guid>
  <pubDate>Tue, 24 Jan 2017 07:34:35 -0600</pubDate>
  <link></link>
  <title><![CDATA[SRF Bioinformatics at JNU]]></title>
  <description><![CDATA[
<p>School of Life Sciences <br />Jawaharlal Nehru University <br />New Delhi 110067</p>

<p>Positions available</p>

<p>Applications were invited from for the following posts in an industry sponsored project. The project entitled "OsHK3b technology and Know How", valid for a period upto February, 2018.</p>

<p>Post 3: Senior Research Fellow (Computational Biologist / Metabolic engineering)</p>

<p>Salary: As per DBT rule.</p>

<p>Duration: All the above posts are purely temporary and liable to be terminated at any time without prior notice or ceased/withdrawn by the funding agency.</p>

<p>Age limit: The upper age limit for SRF shall be 32 years, which is relaxed upto 5 years in the case of candidates belonging to Schedule Castes/Schedule Tribes, Women, Physically Handicapped and OBC applicants.</p>

<p>Essential Qualifications: Masters/B Tech/Mtech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Computational Biology related to Database /portal building &amp; maintenance, high throughput data handling and analysis etc. For M.Sc/B.Tech, Published paper in peer-reviewed Journal and for M.Tech, thesis submission in computational biology is a must. Selection preference will be given to candidates with a good knowledge of Python and/or R. Knowledge of JAVA will also get a special consideration.</p>

<p>Desired Skills: Will be expected to manage ongoing research activities in the project, interact with Experimental group, manage the project data analysis, prepare file reports and associated project work etc. Familiarity with plant systems biology and genomics /metabolite resources related to plant metabolomics is desirable.</p>

<p>1. The post applied for must be clearly written on the Envelope containing the application <br />2. Applications received after last date shall not be entertained, School will not be responsible for any postal delay. <br />3. No application will be accepted via hand delivery or via e-mail. Please send printed &amp; signed applications with detailed CV on or before 31st January, 2017 by post to the following address:</p>

<p>Prof. Ashwani Pareek <br />(Project Investigator) <br />Stress Physiology and Molecular Biology Laboratory (Room No-413), <br />School of Life Sciences, <br />Jawaharlal Nehru University, <br />New Delhi, India – 110067 <br />Email: ashwanipareek@gmail.com</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/30744/binc-2017</guid>
	<pubDate>Wed, 01 Feb 2017 09:36:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/30744/binc-2017</link>
	<title><![CDATA[BINC 2017]]></title>
	<description><![CDATA[<p><span>Pondicherry University,Puducherry,on behalf of Department of Biotechnology, Government of India, conducted the BINC examination in&nbsp;</span><span style="color: blue;">2015 and 2016.&nbsp;</span><span>The objective of this examination is to certify bioinformatics professionals, trained formally as well as self-trained.</span><span style="color: blue;">Registration for BINC 2017 examination will open from January 29,2017 to February 28,2017.</span><span>&nbsp;</span></p><p><span>Pondicherry University, Puducherry has been identified as a nodal agency by the Department of Biotechnology, Govt. of India to coordinate this examination along with nine centres namely, </span></p><p><span>Pune University, Pune; </span></p><p><span>Anna University, Chennai; </span></p><p><span>Bose Institute, Kolkata; </span></p><p><span>Institute of Bioinformatics &amp; Applied Biotechnology, Bangalore; </span></p><p><span>North-Eastern Hill University, Shillong, University of Hyderabad, Hyderabad; </span></p><p><span>University of Kerala, Thiruvananthapuram; </span></p><p><span>Jawaharlal Nehru University, New Delhi and </span></p><p><span>Assam Agricultural University, Guwahati.</span><span style="color: blue;"><strong>&nbsp;</strong></span></p><p><span style="color: blue;"><strong>In the BINC 2015 and 2016 examination, 23 candidates and five candidates were certified respectively.</strong></span><span>&nbsp;DBT has agreed to fund Research fellowships for all the BINC qualified Indian nationals to pursue Ph.D. in Indian Institutes/Universities. </span></p><p><span>Note that the candidate must possess a postgraduate degree(or equivalent) &amp; meet the criteria of the institutes/universities in order to avail research fellowship. </span></p><p><span>In addition, cash prize of Rs. 10,000/- will be awarded to the top 10 BINC qualifiers.</span></p><p><span>More at&nbsp;http://www.pondiuni.edu.in/exams/binc/</span></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30829/mercator</guid>
	<pubDate>Mon, 06 Feb 2017 04:20:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30829/mercator</link>
	<title><![CDATA[Mercator]]></title>
	<description><![CDATA[<p><span>Our basic strategy in building homology maps is to use exons that are orthologous in multiple genomes as map "anchors." Given K genomes, the steps in the map construction are as follows:</span></p>
<ul>
<li>For each genome, obtain a set of exon annotations. These annotations can be a combination of both exon predictions (e.g. Genscan) and annotations that have been experimentally verified (e.g. RefSeq). Ideally, we would like to have these annotations be as sensitive as possible. Specificity is not a concern, as incorrect annotations are not likely not have significant alignments with other gene annotations.</li>
<li>Compare all exons against all exons in other genomes and record significant alignments between exons. Currently, we use&nbsp;<a href="https://www.biostat.wisc.edu/~cdewey/mercator/#refBLAT">BLAT</a>&nbsp;to do this all-vs-all comparison with alignments being performed in protein space.</li>
<li>Construct a graph with each vertex corresponding to a exon and edges between vertices whose corresponding exons have significant alignments.</li>
<li>Identify cliques in this graph. These cliques are potential anchors to be used in the map.</li>
<li>Starting with the largest cliques (those that have exons in all or most of the genomes), join neighboring (adjacent in genomic coordinates, in each genome) cliques to form&nbsp;runs. Smaller cliques that are inconsistent with runs formed by larger cliques are filtered out. After the smallest cliques have been considered, cliques that are not part of a run are discarded.</li>
<li>The extents of each run in each genome are outputted as orthologous segments. The cliques from each run are used to output the exact genomic coordinates of anchors within each orthologous segment. These anchors can be used by genomic alignment programs (such as&nbsp;<a href="https://www.biostat.wisc.edu/~cdewey/mercator/#refMAVID">MAVID</a>) to do a detailed alignment of each orthologous segment.</li>
</ul>
<p>https://www.biostat.wisc.edu/~cdewey/mercator/</p><p>Address of the bookmark: <a href="https://www.biostat.wisc.edu/~cdewey/mercator/" rel="nofollow">https://www.biostat.wisc.edu/~cdewey/mercator/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30897/finestructure-v2-globetrotter</guid>
	<pubDate>Mon, 13 Feb 2017 08:40:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30897/finestructure-v2-globetrotter</link>
	<title><![CDATA[fineSTRUCTURE v2 &amp; GLOBETROTTER]]></title>
	<description><![CDATA[<p>Software available at this site</p>
<div>
<ul>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure_info.html">FineSTRUCTURE version 2</a>, a pipeline for running ChromoPainter and FineSTRUCTURE for population inference. A GUI is available for interpretation. Download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructureR.html">FineSTRUCTURE R scripts</a>, a facility for exploring the results when the GUI is unavailable.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/globetrotter.html">GLOBETROTTER</a>, the admixture dating method based on ChromoPainter. Download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/admixture.html">AdmixturePainting</a>, A set of R tools to inmterpret the results of ADMIXTURE and STRUCTURE-like mixture models.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/radpainter.html">RADpainter</a>, finestructure and ChromoPainter for RAD tag data used for non-model organisms.</li>
<li>Scripts to perform many types of conversion. Included in the main software download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
</ul>
What this page is This page provides information about and downloads for <strong>methodology for Chromosome Painting</strong>. It is not a facility to analyse your genome. Sorry if you were misled by the punchy name!<br> About Chromosome Painting Painting is an efficient way of identifying important haplotype information from dense genotype data. It describes ancestry in an efficient way suitable for a range of further analyses, including population identification and admixture dating.</div><p>Address of the bookmark: <a href="http://paintmychromosomes.com/" rel="nofollow">http://paintmychromosomes.com/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30971/hiveplot</guid>
	<pubDate>Thu, 16 Feb 2017 11:39:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30971/hiveplot</link>
	<title><![CDATA[HivePlot]]></title>
	<description><![CDATA[<p>The&nbsp;<em>hive plot</em>&nbsp;is a rational visualization method for drawing networks. Nodes are mapped to and positioned on radially distributed linear axes &mdash; this mapping is based on network structural properties. Edges are drawn as curved links. Simple and interpretable.</p>
<p>The purpose of the hive plot is to establish a new baseline for visualization of large networks &mdash; a method that is both general and tunable and useful as a starting point in visually exploring network structure.</p>
<p>More at&nbsp;http://www.hiveplot.com/</p><p>Address of the bookmark: <a href="http://www.hiveplot.com/" rel="nofollow">http://www.hiveplot.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33006/avid-a-global-alignment-program</guid>
	<pubDate>Wed, 24 May 2017 05:19:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33006/avid-a-global-alignment-program</link>
	<title><![CDATA[AVID: A Global Alignment Program]]></title>
	<description><![CDATA[<p>A new global alignment method called AVID. The method is designed to be fast, memory efficient, and practical for sequence alignments of large genomic regions up to megabases long. We present numerous applications of the method, ranging from the comparison of assemblies to alignment of large syntenic genomic regions and whole genome human/mouse alignments. We have also performed a quantitative comparison of AVID with other popular alignment tools. To this end, we have established a format for the representation of alignments and methods for their comparison. These formats and methods should be useful for future studies. The tools we have developed for the alignment comparisons, as well as the AVID program, are publicly available. See Web Site References section for AVID Web address and Web addresses for other programs discussed in this paper.</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC430967/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC430967/</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31024/dagchainer-computing-chains-of-syntenic-genes-in-complete-genomes</guid>
	<pubDate>Fri, 17 Feb 2017 16:13:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31024/dagchainer-computing-chains-of-syntenic-genes-in-complete-genomes</link>
	<title><![CDATA[DAGchainer: Computing Chains of Syntenic Genes in Complete Genomes]]></title>
	<description><![CDATA[<p>The DAGchainer software computes chains of syntenic genes found within complete genome sequences. As input, DAGchainer accepts a list of gene pairs with sequence homology along with their genome coordinates. Using a scoring function which accounts for the distance between neighboring genes on each DNA molecule and the BLAST E-value score between homologs, maximally scoring chains of ordered gene pairs are computed and reported. This algorithm can be used to mine large evolutionary conserved regions of genomes between two organisms. Alternatively, by examining colinear sets of homologous genes found within a single genome, segmental genome duplications can be revealed.</p>
<p>This software distribution includes both the DAGchainer utility and a Java-based graphical interface that allows the inputs and outputs to be navigated and interrogated dynamically.</p><p>Address of the bookmark: <a href="http://dagchainer.sourceforge.net/" rel="nofollow">http://dagchainer.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36216/crusview</guid>
	<pubDate>Thu, 12 Apr 2018 09:22:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36216/crusview</link>
	<title><![CDATA[CrusView]]></title>
	<description><![CDATA[<p><span>CrusView&nbsp;is a java based tool for karyotype/genome visualization and comparison of crucifer&nbsp;Species. It also integrates an binary version of KGBassembler and a&nbsp;post-modification step for its assembling result.</span></p><p>Address of the bookmark: <a href="http://www.cmbb.arizona.edu/?page_id=250" rel="nofollow">http://www.cmbb.arizona.edu/?page_id=250</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31205/yasra-reference-based-assembler</guid>
	<pubDate>Wed, 01 Mar 2017 08:32:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31205/yasra-reference-based-assembler</link>
	<title><![CDATA[YASRA: Reference based assembler]]></title>
	<description><![CDATA[<p>YASRA (Yet Another Short Read Assembler) performs comparative assembly of short reads using a reference genome, which can differ substantially from the genome being sequenced. Mapping reads to reference genomes makes use of LASTZ (Harris et al), a pairwise sequence aligner compatible with BLASTZ. Special scoring sets were derived to improve the performance, both in runtime and quality for 454 and Illumina sequence reads.</p>
<p>YASRA uses LASTZ (<a href="http://bx.psu.edu/miller_lab">http://bx.psu.edu/miller_lab</a> for released version and <a href="http://www.bx.psu.edu/%7Ersharris/lastz/newer">http://www.bx.psu.edu/~rsharris/lastz/newer</a> for newer version) for aligning the sequences to the reference genome. Please install LASTZ (the newest version on <a href="http://www.bx.psu.edu/%7Ersharris/lastz/newer">http://www.bx.psu.edu/~rsharris/lastz/newer</a>) and add the LASTZ binary in your executable/binary search path before installing YASRA.</p><p>Address of the bookmark: <a href="https://github.com/aakrosh/YASRA" rel="nofollow">https://github.com/aakrosh/YASRA</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39017/macse-multiple-alignment-of-coding-sequences-accounting-for-frameshifts-and-stop-codons</guid>
	<pubDate>Mon, 18 Feb 2019 04:21:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39017/macse-multiple-alignment-of-coding-sequences-accounting-for-frameshifts-and-stop-codons</link>
	<title><![CDATA[MACSE: Multiple Alignment of Coding SEquences Accounting for Frameshifts and Stop Codons]]></title>
	<description><![CDATA[<p>MACSE aligns coding NT sequences with respect to their AA translation while allowing NT sequences to contain multiple frameshifts and/or stop codons. MACSE is hence the first automatic solution to align protein-coding gene datasets containing non-functional sequences (pseudogenes) without disrupting the underlying codon structure. It has also proved useful in detecting undocumented frameshifts in public database sequences and in aligning next-generation sequencing reads/contigs against a reference coding sequence.</p>
<p>For further details about the underlying algorithm see the original publication:<br><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0022594" target="_new">MACSE: Multiple Alignment of Coding SEquences accounting for frameshifts and stop codons.<br>Vincent Ranwez, S&eacute;bastien Harispe, Fr&eacute;d&eacute;ric Delsuc, Emmanuel JP Douzery<br>PLoS One 2011, 6(9): e22594</a>.</p><p>Address of the bookmark: <a href="https://bioweb.supagro.inra.fr/macse/index.php?menu=releases" rel="nofollow">https://bioweb.supagro.inra.fr/macse/index.php?menu=releases</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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