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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27323?offset=810</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22024/research-associate-bioinformatics-job-position-in-indian-agricultural-statistics-research-institute-iasri-pusa-new-delhi</guid>
  <pubDate>Tue, 14 Apr 2015 11:57:13 -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>Indian Agricultural Statistics Research Institute is inviting applications from indian citizens for recruiting following posts:</p>

<p>Vacancies:<br />Research Associate-02<br />Age Limits:<br />Candidates age limit should be not more than 40 years as on date of interview.<br />Qualification:<br />Candidates should possess Ph.D in Bioinformatics/Agricultural Statistics/Statistics/Computer Science/Computer Application or equivalent.<br />Selection Process:<br />Selection will be based on interview.<br />How to Apply:<br />Eligible candidates may attend for interview along with application in prescribed format, recent passport size photograph pasted on the application form, bio-data, original certificates and self attested copies of relevant documents, all experience certificates, testimonials etc, held at Indian Agricultural Statistics Research Institute, Pusa, New Delhi on 18-04-2015 at 10:30 AM.<br />Last Date:<br />18-04-2015</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36806/manta-rapid-detection-of-structural-variants-and-indels-for-germline-and-cancer-sequencing-applications</guid>
	<pubDate>Mon, 28 May 2018 09:41:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36806/manta-rapid-detection-of-structural-variants-and-indels-for-germline-and-cancer-sequencing-applications</link>
	<title><![CDATA[Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications.]]></title>
	<description><![CDATA[Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for analysis of germline variation in small sets of individuals and somatic variation in tumor/normal sample pairs. Manta discovers, assembles and scores large-scale SVs, medium-sized indels and large insertions within a single efficient workflow.<p>Address of the bookmark: <a href="https://github.com/Illumina/manta" rel="nofollow">https://github.com/Illumina/manta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/22044/binc-sample-question-paper</guid>
	<pubDate>Thu, 16 Apr 2015 09:12:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/22044/binc-sample-question-paper</link>
	<title><![CDATA[BINC Sample Question Paper !!!]]></title>
	<description><![CDATA[<p>BINC sample question paper for round ONE.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/22044" length="1260" type="text/plain" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37498/nextsv-a-meta-caller-for-structural-variants-from-low-coverage-long-read-sequencing-data</guid>
	<pubDate>Mon, 06 Aug 2018 17:24:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37498/nextsv-a-meta-caller-for-structural-variants-from-low-coverage-long-read-sequencing-data</link>
	<title><![CDATA[NextSV: a meta-caller for structural variants from low-coverage long-read sequencing data]]></title>
	<description><![CDATA[<p>NextSV, a meta SV caller and a computational pipeline to perform SV calling from low coverage long-read sequencing data. NextSV integrates three aligners and three SV callers and generates two integrated call sets (sensitive/stringent) for different analysis purpose. The output of NextSV is in ANNOVAR-compatible bed format. Users can easily perform downstream annotation using ANNOVAR and disease gene discovery using Phenolyzer.</p>
<p>&nbsp;</p>
<h2>&nbsp;</h2><p>Address of the bookmark: <a href="https://github.com/Nextomics/NextSV" rel="nofollow">https://github.com/Nextomics/NextSV</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/22068/binc-examination-2015</guid>
	<pubDate>Fri, 17 Apr 2015 03:34:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/22068/binc-examination-2015</link>
	<title><![CDATA[BINC examination 2015 !!!]]></title>
	<description><![CDATA[<p>BioInformatics National Certification (BINC) Examination 2015 organized by Department of Biotechnology, Government of India, New Delhi Pondicherry University, Puducherry</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/22068" length="281577" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37749/d2tools-the-toolbox-for-counting-the-frequency-of-k-tuple-from-sequencing-datasets-and-calculate-the-dissimilarity</guid>
	<pubDate>Thu, 20 Sep 2018 08:38:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37749/d2tools-the-toolbox-for-counting-the-frequency-of-k-tuple-from-sequencing-datasets-and-calculate-the-dissimilarity</link>
	<title><![CDATA[d2Tools: The toolbox for counting the frequency of k-tuple from sequencing datasets and calculate the dissimilarity]]></title>
	<description><![CDATA[<p><code>d2Tools</code>&nbsp;are the toolbox for counting the frequency of K-tuple from sequencing datasets and then calculating the pairwise dissimilarity matrix between samples with the&nbsp;<strong>d2-style</strong>(d2/d2<code>*</code>/d2S representing d2/d2Star/d2shepp, respectively) measures. Hao, Dai, Eucliean, Mahattan, and Chebyshev distance measures are also included in d2Tools.</p>
<p>Manual at&nbsp;https://code.google.com/archive/p/d2-tools/wikis/d2ToolMannual.wiki</p><p>Address of the bookmark: <a href="https://code.google.com/archive/p/d2-tools/" rel="nofollow">https://code.google.com/archive/p/d2-tools/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22234/national-institute-of-biologicals-recruitment-2015</guid>
  <pubDate>Mon, 27 Apr 2015 19:44:45 -0500</pubDate>
  <link></link>
  <title><![CDATA[National Institute of Biologicals Recruitment 2015]]></title>
  <description><![CDATA[
<p>National Institute of Biologicals (NIB), Noida<br />Job Code: 260415(04)Y</p>

<p>National Institute of Biologicals (NIB), Noida invites applications to recruit on vacant posts of Scientist, Training Officer, Administrative Assistant, Stenographer, Junior Engineer, Computer Operator etc. Applications against these Government Jobs can be submitted on or before 01 July 2015.</p>

<p>NIB Vacancy 2015 Details<br />1. Scientist Grade III – 06<br />Qualification: PG degree in the concern field.<br />Age Limit: 35 Years</p>

<p>2. Junior Scientist – 07<br />Qualification: M.Sc. in Microbiology / Clinical Microbiology / Biotechnology/ Bioinformatics/ Biochemistry/Bacteriology/Pharmacology/ Serology / Molecular Biology/Physiology from any recognized University with at least 60% marks.<br />Age Limit: 30 Years</p>

<p>How to Apply: Duly filled-in applications in prescribed application format along with copies of required documents should be reach to: Administrative Officer, National Institute of Biologicals (Ministry of Health &amp; Family Welfare), A-32, Sector-62, Institutional Area, Noida-201309. Click here to obtain application form.</p>

<p>The Last Date to apply to NIB Job is 01 July 2015.</p>

<p>Click here to view details http://nib.gov.in/Advt%20%20%2824.04.2015%29.pdf</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/38649/ngs-platforms-launched-by-bgi%E2%80%99s-mgi-tech</guid>
	<pubDate>Thu, 10 Jan 2019 04:42:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/38649/ngs-platforms-launched-by-bgi%E2%80%99s-mgi-tech</link>
	<title><![CDATA[NGS Platforms launched by BGI’s MGI Tech]]></title>
	<description><![CDATA[<p>MGI Tech Co., Ltd. (MGI), a subsidiary of BGI Group, is committed to enabling effective and affordable healthcare solutions for all. Based on its proprietary technology, MGI produces sequencing devices, equipment, consumables and reagents to support life science research, medicine and healthcare. MGI's multi-omics platforms include genetic sequencing, mass spectrometry and medical imaging. Providing real-time, comprehensive, life-long solutions, its mission&nbsp;is to&nbsp;develop and promote advanced life science tools for future healthcare.</p><p>MGI, a subsidiary of global genomics leader BGI Group, announced pricing and its first early access customer for the new ultra high-throughput sequencer, MGISEQ-T7, saying it has driven down sequencing cost to&nbsp;$5&nbsp;per gigabyte, with exceptionally high accuracy. Such innovations are helping more people to realize the benefits of genomic information.</p><p>In October, MGI launched the MGISEQ-T7, a highly flexible production-scale platform that is the most powerful sequencer to date. It can produce as many as 60 whole human genomes in one day. The instrument sells for&nbsp;$1 million.</p><p>The T7 enables simultaneous but independent operation of up to four flow cells, which means different applications such as single-cell RNA sequencing, whole exome sequencing and whole genome sequencing can be run in different flow cells at the same time. This helps to reduce costs, allowing MGI to offer the most competitive sequencing price in the market.</p><p><span>Powered by DNBseq&trade;, MGISEQ delivers quality data with accuracy for SNP and Indel calling rate of 99.9% and 99%, respectively, along with decreased duplication rate down to less than 2 percent, and almost zero Index mis-assignment rate.</span></p><p><span><span>SOURCE MGI</span></span></p><p>https://www.bgi.com/global/company/news/bgis-mgi-tech-launches-two-new-ngs-platforms/</p><p>http://en.mgitech.cn/</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22429/walk-ins-for-jrf-ans-srf-post-in-nirrh-mumbai</guid>
  <pubDate>Thu, 28 May 2015 19:04:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Walk-ins for JRF ans SRF post in NIRRH, Mumbai]]></title>
  <description><![CDATA[
<p>Title of project- "EXPLORING THE HINGE AND TRANSMEMBRANE REGION OF HUMAN FSHR FOR DESIGN OF SMALL MOLECULE AND PEPTIDOMIMETIC MODULATORS"<br />Name of the Post- Junior Research Fellow<br />No. of vacancy- One<br />Stipend- Rs. 25000/ +30% HRA<br />Essential qualification- Candidate should be Post Graduate Degree in Life Sciences / Bioinformatics /Pharmacology/ Chemistry or any other relevant area of Biology or Graduate Degree in Professional Course with NET qualification or Post Graduate Degree in Professional Course.<br />Desirable- Candidate with Good knowledge of protein structures, docking, MD simulations will be preferred.<br />Age Limit- Not exceeding 28 Years<br />Duration of project- Upto May 2018</p>

<p>Title of project- "Analysis of the structures of known antimicrobial peptides using machine learning algorithms and molecular dynamics simulations".<br />Name of the Post- Senior Research Fellow<br />No. of vacancy- One<br />Stipend- Rs. 14000/ +30% HRA<br />Essential qualification- Candidate should be having M.Sc. degree in Life Sciences / Bioinformatics / Pharmacology/ Chemistry or any other relevant area of Biology and 2 years of research experience.<br />Desirable- Candidate with Good knowledge of protein structures, docking, MD simulations will be preferred.<br />Age Limit- Not exceeding 35 Years<br />Duration of project- Upto April 2016<br />How to Apply- Interested candidates can download the application form from below mentioned link- http://www.nirrh.res.in/links/BiodataForm.pdf<br />Candidate must bring the filled up application form along with all the relevant documents in original and one set of attested photocopies of the same and one passport size recent colour photograph.</p>

<p>Ref. - http://www.nirrh.res.in/links/job_jrf-srf.htm</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</guid>
	<pubDate>Sat, 25 Jan 2020 13:28:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</link>
	<title><![CDATA[DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.]]></title>
	<description><![CDATA[<p><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.</span></p>
<p><span><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on&nbsp;</span><a href="https://github.com/google/nucleus">Nucleus</a><span>, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the&nbsp;</span><a href="https://www.tensorflow.org/">TensorFlow</a><span>&nbsp;machine learning framework.</span></span></p>
<p><span><a href="https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html">https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html</a></span></p>
<p><span><a href="https://www.biorxiv.org/content/10.1101/092890v6">https://www.biorxiv.org/content/10.1101/092890v6</a></span></p>
<p><span><img src="https://4.bp.blogspot.com/-2KlXZO60sWE/WiGc8qlZfxI/AAAAAAAACOs/s1pNiKI8jsAvJLr1E_po5udDO8eObm_awCLcBGAs/s640/image3.png" width="640" height="427" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/google/deepvariant" rel="nofollow">https://github.com/google/deepvariant</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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