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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27427?offset=630</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22567/rosalind-problem-solution-with-perl</guid>
	<pubDate>Tue, 09 Jun 2015 23:35:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22567/rosalind-problem-solution-with-perl</link>
	<title><![CDATA[Rosalind Problem Solution with Perl]]></title>
	<description><![CDATA[<p>Rosalind is a platform for learning bioinformatics and programming through problem solving. <a href="http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track">Take a tour</a> to get the hang of how Rosalind works.</p><p>Bioinformatics Textbook Track</p><p>Find more about Rosalind puzzle at http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track</p><p>I will provide solution of all the Rosalind problem with Perl for community.</p><p>Check out the right sidebar for more links ...</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/33486/quick-next-generation-sequencing-ngs-terms-definition</guid>
	<pubDate>Fri, 09 Jun 2017 04:52:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/33486/quick-next-generation-sequencing-ngs-terms-definition</link>
	<title><![CDATA[Quick next generation sequencing (NGS) terms definition]]></title>
	<description><![CDATA[<p><strong>fragment size:</strong><span>&nbsp;the Illumina WGS protocol generates paired-end reads from both ends of longer fragments. The lengths of these fragments are assumed to be sampled from a normal distribution. Therefore, in the absence of structural variants, mapping locations of the paired ends span within an interval [&delta;min,&delta;max]. Most (&gt;90%) of paired-end reads are sampled from no-SV regions, therefore the fragment size distribution can be learned empirically for each WGS data set separately.</span><br /><br /><strong>concordant reads:</strong><span>&nbsp;a read pair is called concordant if they can be mapped to the reference genome as &ldquo;expected&rdquo;: (a) mapped to opposing strands where the upstream read is mapped to the forward strand and the downstream read is mapped to the reverse strand2, (b) the distance between ends is between the minimum and maximum expected fragment size.</span><br /><br /><strong>discordant reads:</strong><span>&nbsp;briefly, any non-concordant read pair is considered discordant. Note that, by definition, the discordant read pairs signal potential SVs. The sequence signature produced by these type of reads is known as read-pair signature.</span><br /><br /><strong>split reads:</strong><span>&nbsp;a read that can only be mapped to the reference genome by breaking into two sub-reads is called a split-read. These types of reads also indicate a potential SV or a short insertion or deletion (indel).</span><br /><br /><strong>read depth:</strong><span>&nbsp;number of reads that map within a region of the genome. Overall genome-wide read depth is also referred to as depth of coverage. It is expected that the number of reads that &ldquo;cover&rdquo; each base-pair to follow a Poisson distribution. Therefore, if the read depth over a certain region deviates significantly from this distribution, it signals for a potential copy number variation (CNV).</span></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22616/research-associate-manit-allahabad-uttar-pradesh</guid>
  <pubDate>Fri, 12 Jun 2015 05:44:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate MANIT - Allahabad, Uttar Pradesh]]></title>
  <description><![CDATA[
<p>Applications are invited from Indian nationals for the post of Research Assistant (on contract) in research project entitled “Identification of novel drug targets in Aspergillus fumigatus genome prioritized by essentiality based screening and rational designing of new antifungal compounds” sanction order no. CST/238 dated 12/05/2015 sponsored by Council of Science and Technology U.P. </p>

<p>The duly completed application on prescribed format along with copies of supporting documents must reach to: Office of the Dean (Research &amp; Consultancy), Motilal Nehru National Institute of Technology, Allahabad-211004 on or before 03/07/2015. </p>

<p>The position is purely temporary and will be governed by the funding agency rules &amp; service conditions of Office of the Dean (Research &amp; Consultancy), MNNIT Allahabad. </p>

<p>For detail advertisement see: www.mnnit.ac.in/images/newstories/Advertisement_for_the_post_of_Research_Assistant_in_UPCST_Project_of_Biotechnology_Department.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</guid>
	<pubDate>Tue, 08 May 2018 04:58:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</link>
	<title><![CDATA[MIX: Combining multiple assemblies from NGS data]]></title>
	<description><![CDATA[<p>Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.</p>
<p>The Mix algorithm, approach and results were published in BMC bioinformatics :&nbsp;<a href="http://www.biomedcentral.com/1471-2105/14/S15/S16">http://www.biomedcentral.com/1471-2105/14/S15/S16</a>.</p><p>Address of the bookmark: <a href="https://github.com/cbib/MIX" rel="nofollow">https://github.com/cbib/MIX</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22779/research-associate-at-international-centre-for-genetic-engineering-and-biotechnology-icgeb</guid>
  <pubDate>Wed, 17 Jun 2015 18:49:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate at International Centre for Genetic Engineering and Biotechnology (ICGEB)]]></title>
  <description><![CDATA[
<p>Research Associate<br />International Centre for Genetic Engineering and Biotechnology (ICGEB)<br />Address: Aruna Asaf Ali Marg, Jawaharlal Nehru University, New Delhi<br />Postal Code: 110067<br />City: New Delhi<br />State: Delhi<br />Qualifications: Experience in many docking softwares and operating systems is essential. Additional experience in bioinformatics and computational biology tools will be useful.<br />Details will be available at: http://www.icgeb.org/vacancies.html<br /> <br />How To Apply: Submit curriculum vitae to: sb.icgeb@gmail.com<br />Last Date: 5 July 2015</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</guid>
	<pubDate>Fri, 08 Jun 2018 10:47:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</link>
	<title><![CDATA[HALC: High throughput algorithm for long read error correction]]></title>
	<description><![CDATA[HALC, a high throughput algorithm for long read error correction. HALC aligns the long reads to short read contigs from the same species with a relatively low identity requirement so that a long read region can be aligned to at least one contig region, including its true genome region’s repeats in the contigs sufficiently similar to it (similar repeat based alignment approach)

HALC was able to obtain 6.7-41.1% higher throughput than the existing algorithms while maintaining comparable accuracy. The HALC corrected long reads can thus result in 11.4-60.7% longer assembled contigs than the existing algorithms.<p>Address of the bookmark: <a href="https://github.com/lanl001/halc" rel="nofollow">https://github.com/lanl001/halc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22788/research-associate-bioinformatics-job-position-in-indian-agricultural-statistics-research-institute-iasri-pusa-new-delhi</guid>
  <pubDate>Wed, 17 Jun 2015 20:48:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate Bioinformatics job position in Indian Agricultural Statistics Research Institute (IASRI), Pusa, New Delhi]]></title>
  <description><![CDATA[
<p>Research Associate Statistics</p>

<p>Eligibility : M Phil / Phd, MSc</p>

<p>Location : Delhi</p>

<p>Last Date : 27 Jun 2015</p>

<p>Hiring Process : Walk - In<br />Indian Agricultural Statistics Research Institute (IASRI) - Job DetailsDate of posting:03 Jun 15</p>

<p>Research Associate Statisticsjob position in Indian Agricultural Statistics Research Institute (IASRI)<br />on purely contractual temporary basis</p>

<p>Project : “ICAR-Network Project of Transgenic in Crops”</p>

<p>Qualification : Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent OR Post-Graduation in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent with 1st Division or 60% marks or equivalent with at least two years of research experience.</p>

<p>No.of Post: 01</p>

<p>Emoluments for RA: Consolidated Rs. 24000/- per month + 30% HRA for Ph.D holders and consolidated Rs. 23000/- per month + 30% HRA for Master Degree.</p>

<p>Age Limit : 40 years<br />How to apply</p>

<p>Walk-in-interview will be held on 27th June 2015, 10.30 A.M at IASRI, Pusa, New Delhi</p>

<p>More at http://iasri.res.in/employment/employment.htm</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/28051/convert-ensembl-gtf-to-annotation-table-geneid-genesymbol-genewisechrlocation-geneclass-strand-raw</guid>
	<pubDate>Fri, 24 Jun 2016 18:08:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/28051/convert-ensembl-gtf-to-annotation-table-geneid-genesymbol-genewisechrlocation-geneclass-strand-raw</link>
	<title><![CDATA[Convert EnsEMBL GTF to Annotation table (Geneid, GeneSymbol, GeneWiseChrLocation, GeneClass, Strand) Raw]]></title>
	<description><![CDATA[<p><strong>Bash Script source:</strong></p><p>https://gist.github.com/santhilalsubhash/367befcf5216be4b1fd9</p><p>&nbsp;</p><p><strong>Information</strong>:</p><p>This script converts EnsEMBL GTF (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF">https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF</a>) file to annotation table format. It generated two files<br />1) Transcript wise chromosome location with information about transcripts (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt">https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt</a>)<br />2) Gene wise chromosome location with information about genes (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt">https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt</a>)</p><p>Note: You can download GTF files from&nbsp;<a href="http://www.ensembl.org/info/data/ftp/index.html">http://www.ensembl.org/info/data/ftp/index.html</a></p>]]></description>
	<dc:creator>EagleEye</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22944/icgeb-bioinformatics-research-associate-vacancy</guid>
  <pubDate>Thu, 25 Jun 2015 20:41:00 -0500</pubDate>
  <link></link>
  <title><![CDATA[ICGEB Bioinformatics Research Associate Vacancy]]></title>
  <description><![CDATA[
<p>Research Associate Position at ICGEB, New Delhi with Dr. Amit Sharma</p>

<p>Starting 15th July 2015, the position relates to a project specifically for in silico drug docking, screening, design, optimisation and linkage with active chemists. </p>

<p>Experience in many docking softwares and operating systems is essential. </p>

<p>Additional experience in bioinformatics and computational biology tools will be useful. </p>

<p>Submit curriculum vitae to: sb.icgeb@gmail.com</p>

<p>Closing date: 5 July 2015</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37830/nquire-a-statistical-framework-for-ploidy-estimation-using-next-generation-sequencing</guid>
	<pubDate>Thu, 04 Oct 2018 05:23:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37830/nquire-a-statistical-framework-for-ploidy-estimation-using-next-generation-sequencing</link>
	<title><![CDATA[nQuire: a statistical framework for ploidy estimation using next generation sequencing]]></title>
	<description><![CDATA[<p>nQuire provides a statistical framework to study organisms with intraspecific variation in ploidy. nQuire is likely to be useful in epidemiological studies of pathogens, artificial selection experiments, and for historical or ancient samples where intact nuclei are not preserved. It is implemented as a stand-alone Linux command line tool in the C programming language and is available at https://github.com/clwgg/nQuireunder the MIT license.</p><p>Address of the bookmark: <a href="https://github.com/clwgg/nQuireunder" rel="nofollow">https://github.com/clwgg/nQuireunder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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