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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30149?offset=1200</link>
	<atom:link href="https://bioinformaticsonline.com/related/30149?offset=1200" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<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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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22235/project-fellow-bioinformatics-at-central-drug-research-institute</guid>
  <pubDate>Mon, 27 Apr 2015 20:15:45 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Fellow Bioinformatics at Central Drug Research Institute]]></title>
  <description><![CDATA[
<p>Project Fellow (Bioinformatics)<br />Central Drug Research Institute<br />Address: Chattar Manzil, M.G.Road, Kaisarbagh<br />Postal Code: 226001<br />City: Lucknow<br />State: Uttar Pradesh<br />Pay Scale: Rs.16,000/- (fixed) p.m.<br />Educational Requirements: M.Sc. in Bioinformatics with 55% marks for Gen. &amp; OBC and 50% marks for SC/ST candidates, Physically and Visually handicapped candidates<br />Experience Requirements: Experience in computer-assisted scientific research in the area of Drug Design including Bio- molecular modeling and simulation studies, Virtual screening, pharmacophore perception, QSAR etc. Familiarity with Linux/Unixbased computer systems and required to participate and contribute to the development and application of computational models for the design and discovery of novel molecules as inhibitors or chemical probes<br />Details will be available at: http://cdriindia.org/uploaded/advt_no01-2015.pdf</p>

<p>How To Apply: Eligible candidates required to report for the Interview at 9:00 A.M. sharp on 11-05-2015 (For Position Code No. 001 to 009) and 12-05-2015 (For Position Code No. 010 to 016). Candidates reporting after 10:00 A.M will not be allowed to attend the interview. Eligible candidates may appear before the Selection Committee for interview on the date and time mentioned above at CDRI, B.S. 10/1, Sector 10, Jankipuram Extension, Sitapur Road, Lucknow-226031. Eligible candidates must bring with them duly filled up application form (which can be downloaded from our website www.cdriindia.org), along with Original certificates as well as attested copies of certificates of examinations starting from matriculation, date of birth, caste certificate (in case of SC/ST/OBC) experience certificate, publication, if any and recent passport size photograph etc. Original documents are essential for verification of the particulars quoted by the candidate in the application form and candidate failed to produce original documents at the time of verification, shall not be allowed to attend the interview. Any request for relaxation in this regard shall not be entertained.<br />Detail of Interview: 11-05-2015<br />Age Limit: 28 Years</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41893/sunbeam-a-robust-extensible-metagenomics-pipeline</guid>
	<pubDate>Thu, 18 Jun 2020 06:58:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41893/sunbeam-a-robust-extensible-metagenomics-pipeline</link>
	<title><![CDATA[sunbeam: A robust, extensible metagenomics pipeline]]></title>
	<description><![CDATA[<p><span>Sunbeam is a pipeline written in&nbsp;</span><a href="http://snakemake.readthedocs.io/">snakemake</a><span>&nbsp;that simplifies and automates many of the steps in metagenomic sequencing analysis. It uses&nbsp;</span><a href="http://conda.io/">conda</a><span>&nbsp;to manage dependencies, so it doesn't have pre-existing dependencies or admin privileges, and can be deployed on most Linux workstations and clusters. To read more, check out&nbsp;</span><a href="https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-019-0658-x">our paper in Microbiome</a><span>.</span></p>
<p><span><a href="https://sunbeam.readthedocs.io/en/latest/">https://sunbeam.readthedocs.io/en/latest/</a></span></p><p>Address of the bookmark: <a href="https://github.com/sunbeam-labs/sunbeam" rel="nofollow">https://github.com/sunbeam-labs/sunbeam</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22269/school-of-life-sciences-jawaharlal-nehru-university-vacancy-of-jrf-srf-ra-in-csir-funded-project</guid>
  <pubDate>Wed, 29 Apr 2015 21:26:19 -0500</pubDate>
  <link></link>
  <title><![CDATA[School of Life Sciences, Jawaharlal Nehru University vacancy of JRF / SRF / RA in CSIR funded Project]]></title>
  <description><![CDATA[
<p>School of Life Sciences, Jawaharlal Nehru University has issued notification dated 27.04.2015 to fill the vacancy of JRF / SRF / RA in CSIR funded Projec entitled "Structural and functional characterization of serine biosynthetic pathway enzymes from entamoeba histolytica". It is good chance to get job with IITKGP and brighten your future. Learn eligibility criteria and apply on or before 08.05.2015.</p>

<p>Employer:	Jawaharlal Nehru University<br />Address:	Dr. S. Gourinath, Principal Investigator, School Of Life Sciences, Jawaharlal Nehru University, New Delhi-110067<br />Email:	not mentioned / provided for this job post<br />URL:	http://www.jnu.ac.in/Career/currentjobs.htm<br />Phone:	011 2674 2575<br />Skills:	not mentioned / required for this job post<br />Experience:	Experience in molecular biology, structural biology and bioinformatics is desired<br />Education:	M.Sc. in any field of life sciences.<br />Job Location:	New Delhi, Delhi, India   (View Jobs in New Delhi,   Jobs in Delhi,   Jobs in India)</p>

<p>Job Description: School of Life Sciences, Jawaharlal Nehru University vacancy of JRF / SRF / RA in CSIR funded Projec</p>

<p>Name of the Post: JRF / SRF / RA</p>

<p>Salary: As per rules</p>

<p>Required Job Profile:</p>

<p>Candidate must possess M.Sc. in any field of life sciences.</p>

<p>Desired Job Profile:</p>

<p>Candidate having NET - CSIR or UGC and experience in molecular biology, structural biology and bioinformatics is desired and experience with publication is preferred.</p>

<p>How to apply:</p>

<p>Eligible and interested candidates should need to apply with complete details to the above mentioned address on or before 08.05.2015.</p>

<p>Refer to http://www.jnu.ac.in/Career/currentjobs.htm</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42413/liftoff-an-accurate-gff3gtf-lift-over-pipeline</guid>
	<pubDate>Sun, 20 Dec 2020 01:36:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42413/liftoff-an-accurate-gff3gtf-lift-over-pipeline</link>
	<title><![CDATA[Liftoff: An accurate GFF3/GTF lift over pipeline]]></title>
	<description><![CDATA[<p><span>Liftoff is a tool that accurately maps annotations in GFF or GTF between assemblies of the same, or closely-related species. Unlike current coordinate lift-over tools which require a pre-generated &ldquo;chain&rdquo; file as input, Liftoff is a standalone tool that takes two genome assemblies and a reference annotation as input and outputs an annotation of the target genome.</span></p><p>Address of the bookmark: <a href="https://github.com/agshumate/Liftoff" rel="nofollow">https://github.com/agshumate/Liftoff</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22287/research-fellows-at-aimscs-hyderabad</guid>
  <pubDate>Wed, 06 May 2015 06:23:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Fellows at AIMSCS, Hyderabad]]></title>
  <description><![CDATA[
<p>C.R.Rao Advanced Institute of Mathematics, Statistics and Computer Science (AIMSCS) - Hyderabad, Andhra Pradesh<br />Advertisement No.: 5/2015</p>

<p>Research Fellows Systems Biology job vacancy in C.R.Rao Advanced Institute of Mathematics, Statistics and Computer Science (AIMSCS)</p>

<p>JRF : Qualification - M. Sc in Bioinformatics, Systems Biology, M. Sc statistics, or M. Tech in Bioinformatics,</p>

<p>Pay Scale : Rs. 25,000</p>

<p>SRF : Qualification- Qualification prescribed for JRF with 2 years of research experience.</p>

<p>Pay Scale : Rs. 28,000*</p>

<p>No.of Post: 2</p>

<p>Desirable: Candidates should have strong background in Computational biology, bioinformatics, statistics and algorithmic development. In addition to that previous experience of working on Linux, bio-informatics, NGS data analysis and Basic knowledge of biology is desirable. Programming on any one of the programming languages (C, C++, perl, python) and statistical framework (e.g. R, matlab, etc.) is highly desirable.</p>

<p>More at http://www.crraoaimscs.org/jrf_application_form_2015.pdf</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43384/lncpipea-nextflow-based-pipeline-for-comprehensive-analyses-of-long-non-coding-rnas-from-rna-seq-datasets</guid>
	<pubDate>Fri, 17 Sep 2021 01:57:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43384/lncpipea-nextflow-based-pipeline-for-comprehensive-analyses-of-long-non-coding-rnas-from-rna-seq-datasets</link>
	<title><![CDATA[LncPipe:A Nextflow-based pipeline for comprehensive analyses of long non-coding RNAs from RNA-seq datasets]]></title>
	<description><![CDATA[<p><span>The pipeline was developed based on a popular workflow framework&nbsp;</span><a href="https://github.com/nextflow-io/nextflow">Nextflow</a><span>, composed of four core procedures including reads alignment, assembly, identification and quantification. It contains various unique features such as well-designed lncRNAs annotation strategy, optimized calculating efficiency, diversified classification and interactive analysis report.&nbsp;</span><a href="https://github.com/likelet/LncPipe">LncPipe</a><span>&nbsp;allows users additional control in interuppting the pipeline, resetting parameters from command line, modifying main script directly and resume analysis from previous checkpoint.</span></p>
<p>Ref&nbsp;https://www.lncrnablog.com/lncpipe-a-nextflow-based-pipeline-for-identification-and-analysis-of-long-non-coding-rnas-from-rna-seq-data/</p>
<p><img src="https://ars.els-cdn.com/content/image/1-s2.0-S1673852718301176-gr1.jpg" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/likelet/LncPipe" rel="nofollow">https://github.com/likelet/LncPipe</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22388/perl-one-liner-basics</guid>
	<pubDate>Sun, 24 May 2015 09:28:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22388/perl-one-liner-basics</link>
	<title><![CDATA[Perl One liner basics !!]]></title>
	<description><![CDATA[<p>Perl has a ton of command line switches (see perldoc perlrun), but I'm just going to cover the ones you'll commonly need to debug code. The most important switch is -e, for execute (or maybe "engage" :) ). The -e switch takes a quoted string of Perl code and executes it. For example:<br /><br />$ perl -e 'print "Hello, World!\n"'<br />Hello, World!<br /><br />It's important that you use single-quotes to quote the code for -e. This usually means you can't use single-quotes within the one liner code. If you're using Windows cmd.exe or PowerShell, you must use double-quotes instead.<br /><br />I'm always forgetting what Perl's predefined special variables do, and often test them at the command line with a one liner to see what they contain. For instance do you remember what $^O is?<br /><br />$ perl -e 'print "$^O\n"'<br />linux<br /><br />It's the operating system name. With that cleared up, let's see what else we can do. If you're using a relatively new Perl (5.10.0 or higher) you can use the -E switch instead of -e. This turns on some of Perl's newer features, like say, which prints a string and appends a newline to it. This saves typing and makes the code cleaner:<br /><br />$ perl -E 'say "$^O"'<br />linux<br /><br />Pretty handy! say is a nifty feature that you'll use again and again.</p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44768/tritex-a-computational-pipeline-for-chromosome-scale-assembly-of-plant-genomes</guid>
	<pubDate>Fri, 14 Feb 2025 10:53:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44768/tritex-a-computational-pipeline-for-chromosome-scale-assembly-of-plant-genomes</link>
	<title><![CDATA[TRITEX, a computational pipeline for chromosome-scale assembly of plant genomes]]></title>
	<description><![CDATA[<p><span>This is the documentation of TRITEX, a computational pipeline for chromosome-scale assembly of plant genomes. It was developed in the research group Domestication Genomics at the Leibniz Institute of Plant Genetics and Crop Research (IPK) Gatersleben.</span></p><p>Address of the bookmark: <a href="https://tritexassembly.bitbucket.io/" rel="nofollow">https://tritexassembly.bitbucket.io/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22403/ryan-e-mills-lab</guid>
  <pubDate>Tue, 26 May 2015 09:29:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Ryan E. Mills Lab]]></title>
  <description><![CDATA[
<p>Our research group is primarily focused on the analysis of whole genome sequence data to identify genetic variation (primarily structural variation) and examine their potential functional impact in disease phenotypes. We are particularly interested in analyzing complex regions of the genome that are not easily resolved through modern sequencing approaches and which may exhibit interesting mechanistic origins.</p>

<p>We are also interested in the large-scale integration of genomic, expression, methylation and proteomic data sets, as well as the application of whole genome sequence analysis in clinical diagnostics. </p>

<p>More at http://millslab.ccmb.med.umich.edu/index.html</p>
]]></description>
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