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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27076?offset=430</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42972/list-of-bioinformatics-workflow-management-tools</guid>
	<pubDate>Sat, 20 Mar 2021 00:15:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42972/list-of-bioinformatics-workflow-management-tools</link>
	<title><![CDATA[List of bioinformatics workflow management tools !]]></title>
	<description><![CDATA[<h3>Here are list of&nbsp;Workflow Managers</h3><ul>
<li><span><a href="https://github.com/pcingola/BigDataScript">BigDataScript</a></span>&nbsp;&ndash; A cross-system scripting language for working with big data pipelines in computer systems of different sizes and capabilities. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/25189778">paper-2014</a>&nbsp;|&nbsp;<a href="https://pcingola.github.io/BigDataScript">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/ssadedin/bpipe">Bpipe</a></span>&nbsp;&ndash; A small language for defining pipeline stages and linking them together to make pipelines. [&nbsp;<a href="http://docs.bpipe.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/common-workflow-language/common-workflow-language">Common Workflow Language</a></span>&nbsp;&ndash; a specification for describing analysis workflows and tools that are portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments. [&nbsp;<a href="http://www.commonwl.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/broadinstitute/cromwell">Cromwell</a></span>&nbsp;&ndash; A Workflow Management System geared towards scientific workflows. [&nbsp;<a href="https://cromwell.readthedocs.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/galaxyproject">Galaxy</a></span>&nbsp;&ndash; a popular open-source, web-based platform for data intensive biomedical research. Has several features, from data analysis to workflow management to visualization tools. [&nbsp;<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030816">paper-2018</a>&nbsp;|&nbsp;<a href="https://galaxyproject.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/nextflow-io/nextflow">Nextflow</a>&nbsp;(recommended)</span>&nbsp;&ndash; A fluent DSL modelled around the UNIX pipe concept, that simplifies writing parallel and scalable pipelines in a portable manner. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29412134">paper-2018</a>&nbsp;|&nbsp;<a href="http://nextflow.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/cgat-developers/ruffus">Ruffus</a></span>&nbsp;&ndash; Computation Pipeline library for python widely used in science and bioinformatics. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/20847218">paper-2010</a>&nbsp;|&nbsp;<a href="http://www.ruffus.org.uk/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/SeqWare/seqware">SeqWare</a></span>&nbsp;&ndash; Hadoop Oozie-based workflow system focused on genomics data analysis in cloud environments. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/21210981">paper-2010</a>&nbsp;|&nbsp;<a href="https://seqware.github.io/">web</a>&nbsp;]</li>
<li><span><a href="https://bitbucket.org/snakemake">Snakemake</a></span>&nbsp;&ndash; A workflow management system in Python that aims to reduce the complexity of creating workflows by providing a fast and comfortable execution environment. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29788404">paper-2018</a>&nbsp;|&nbsp;<a href="https://snakemake.readthedocs.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/broadinstitute/wdl">Workflow Descriptor Language</a></span>&nbsp;&ndash; Workflow standard developed by the Broad. [&nbsp;<a href="https://software.broadinstitute.org/wdl">web</a>&nbsp;]</li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10460/assistant-professor-at-jawaharlal-nehru-university-in-delhi</guid>
  <pubDate>Wed, 07 May 2014 00:29:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor at Jawaharlal Nehru University in Delhi]]></title>
  <description><![CDATA[
<p>Advt. No. RC/48/2014</p>

<p>SCHOOL OF COMPUTATIONAL AND INTEGRATIVE SCIENCES (SC&amp;IS)</p>

<p>ESSENTIAL QUALIFICATION : - M.Sc./M.Tech. in Physics/ Chemistry/ Biology/ Mathematics/ Statistics/ Bioinformatics/ Computational Biology. Ph.D. in the broad areas of Bioinformatics/ Computational Biology. Candidates must have demonstrated capabilities in terms of high impact research publications in either of the above mentioned areas.</p>

<p>Scale of Pay : - 15600-39100/- (PB-III) AGP Rs. 6000/-</p>

<p>For more details on Centre/School, Specializations etc. please visit JNU website www.jnu.ac.in or contact Section Officer, Room Nos. 131-132, Recruitment Cell, Administrative Block, JNU, New Delhi – 110067, Email: recruitmentjnu2013@gmail.com The last date for the receipt of application is 15 May, 2014.</p>

<p>http://www.jnu.ac.in/Career/</p>

<p>http://www.jnu.ac.in/Career/ADVTNo_RC_48_2014.pdf<br />Last Apply Date:</p>

<p>15 May 2014</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</guid>
	<pubDate>Thu, 04 Oct 2018 16:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</link>
	<title><![CDATA[VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules]]></title>
	<description><![CDATA[<p>VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.</p>
<h5>&nbsp;</h5><p>Address of the bookmark: <a href="https://github.com/broadinstitute/VariantBam" rel="nofollow">https://github.com/broadinstitute/VariantBam</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/10749/memories-can-be-passed-down-through-dna</guid>
	<pubDate>Sat, 10 May 2014 21:24:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/10749/memories-can-be-passed-down-through-dna</link>
	<title><![CDATA[Memories Can Be Passed Down Through DNA]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/tbPwzII_g6o" frameborder="0" allowfullscreen></iframe>The premise of Assassin's Creed is the reliving of other people's memories stored inside DNA. Well scientists have found that in mice, it actually happens! Anthony is joined by special guest and our friend Tara Long from Hard Science to explain how this process works, and if it might apply to humans as well.

Read More: 
Parental olfactory experience influences behavior and neural structure in subsequent generations
http://www.nature.com/neuro/journal/vaop/ncurrent/abs/nn.3594.html
"Using olfactory molecular specificity, we examined the inheritance of parental traumatic exposure, a phenomenon that has been frequently observed, but not understood."

What Is Epigenetics?
http://www.sciencemag.org/content/330/6004/611
"The cells in a multicellular organism have nominally identical DNA sequences (and therefore the same genetic instruction sets), yet maintain different terminal phenotypes. This nongenetic cellular memory, which records developmental and environmental cues (and alternative cell states in unicellular organisms), is the basis of epi-(above)-genetics."

Epigenetics
http://en.wikipedia.org/wiki/Epigenetics

Watch More:
How to Change Your Genes
https://www.youtube.com/watch?v=B5DU9lgbsSE
TestTube Wild Card
http://testtube.com/dnews/dnews-231-how-too-many-screens-affect-our-brain?utm_source=YT&utm_medium=DNews&utm_campaign=DNWC
Is Sexiness Hereditary?
https://www.youtube.com/watch?v=z6STRCncvM8
____________________

DNews is dedicated to satisfying your curiosity and to bringing you mind-bending stories & perspectives you won't find anywhere else! New videos twice daily. 

Watch More DNews on TestTube http://testtube.com/dnews

Subscribe now! http://www.youtube.com/subscription_center?add_user=dnewschannel

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DNews on Facebook http://facebook.com/dnews

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Discovery News http://discoverynews.com]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</guid>
	<pubDate>Tue, 14 Jan 2020 06:47:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</link>
	<title><![CDATA[Shasta long read assembler]]></title>
	<description><![CDATA[<p>The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>&nbsp;flow cells.</p>
<p>Computational methods used by the Shasta assembler include:</p>
<ul>
<li>Using a&nbsp;<a href="https://en.wikipedia.org/wiki/Run-length_encoding">run-length</a>&nbsp;representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.</li>
<li>Using in some phases of the computation a representation of the read sequence based on&nbsp;<em>markers</em>, a fixed subset of short k-mers (k &asymp; 10).</li>
</ul>
<p>More at&nbsp;<a href="https://chanzuckerberg.github.io/shasta/index.html">https://chanzuckerberg.github.io/shasta/index.html</a></p><p>Address of the bookmark: <a href="https://github.com/chanzuckerberg/shasta" rel="nofollow">https://github.com/chanzuckerberg/shasta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping</guid>
	<pubDate>Wed, 29 Jan 2020 06:29:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping</link>
	<title><![CDATA[Understanding your reads and mapping !]]></title>
	<description><![CDATA[<p>One of the best tutorial for beginners ...</p>
<p>https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html</p><p>Address of the bookmark: <a href="https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html" rel="nofollow">https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<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/34400/ioniser-tools-for-the-quality-assessment-of-data-produced-by-oxford-nanopore%E2%80%99s-minion-sequencer</guid>
	<pubDate>Thu, 23 Nov 2017 10:24:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34400/ioniser-tools-for-the-quality-assessment-of-data-produced-by-oxford-nanopore%E2%80%99s-minion-sequencer</link>
	<title><![CDATA[IONiseR:  tools for the quality assessment of data produced by Oxford Nanopore’s MinION sequencer]]></title>
	<description><![CDATA[<p>This package is intended to provide tools for the quality assessment of data produced by Oxford Nanopore&rsquo;s MinION sequencer. It includes a functions to generate a number plots for examining the statistics that we think will be useful for this task.</p>
<p>However, nanopore sequencing is an emerging and rapidly developing technology. It is not clear what will be most informative. We hope that&nbsp;<code>IONiseR</code>&nbsp;will provide a framework for visualisation of metrics that we haven&rsquo;t thought of, and welcome feedback at&nbsp;<a href="mailto:mike.smith@embl.de" target="_blank">mike.smith@embl.de</a>.</p>
<p>If you&rsquo;re not interested in the quality assement of the raw or event level data, and want to jump straight to the getting FASTQ format files from fast5 files you can go straight to the final section of this document.</p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/IONiseR/inst/doc/IONiseR.html" rel="nofollow">https://www.bioconductor.org/packages/devel/bioc/vignettes/IONiseR/inst/doc/IONiseR.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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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