<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27331?offset=1080</link>
	<atom:link href="https://bioinformaticsonline.com/related/27331?offset=1080" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38749/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</guid>
	<pubDate>Sun, 20 Jan 2019 06:34:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38749/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</link>
	<title><![CDATA[ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information]]></title>
	<description><![CDATA[<p><span>ClipCrop for detecting SVs with single-base resolution using soft-clipping information. A soft-clipped sequence is an unmatched fragment in a partially mapped read. To assess the performance of ClipCrop with other SV-detecting tools, we generated various patterns of simulation data &ndash; SV lengths, read lengths, and the depth of coverage of short reads &ndash; with insertions, deletions, tandem duplications, inversions and single nucleotide alterations in a human chromosome.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/shinout/clipcrop" rel="nofollow">https://github.com/shinout/clipcrop</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>

<item>
  <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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40465/airlift-a-methodology-and-tool-for-comprehensively-moving-mappings-and-annotations-from-one-genome-to-another-similar-genome</guid>
	<pubDate>Mon, 23 Dec 2019 10:20:13 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40465/airlift-a-methodology-and-tool-for-comprehensively-moving-mappings-and-annotations-from-one-genome-to-another-similar-genome</link>
	<title><![CDATA[AirLift, a methodology and tool for comprehensively moving mappings and annotations from one genome to another similar genome]]></title>
	<description><![CDATA[<p>We propose AirLift, a methodology and tool for comprehensively moving mappings and annotations from one genome to another similar genome while maintaining the accuracy of a full mapper.</p><p>Address of the bookmark: <a href="https://github.com/CMU-SAFARI/AirLift" rel="nofollow">https://github.com/CMU-SAFARI/AirLift</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41046/iseqqc-a-tool-for-expression-based-quality-control-in-rna-sequencing</guid>
	<pubDate>Sun, 16 Feb 2020 08:47:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41046/iseqqc-a-tool-for-expression-based-quality-control-in-rna-sequencing</link>
	<title><![CDATA[iSeqQC: a tool for expression-based quality control in RNA sequencing]]></title>
	<description><![CDATA[<p><span>iSeqQC, an expression-based QC tool that detects outliers either produced due to variable laboratory conditions or due to dissimilarity within a phenotypic group. iSeqQC implements various statistical approaches including unsupervised clustering, agglomerative hierarchical clustering and correlation coefficients to provide insight into outliers.</span></p>
<p><a href="http://cancerwebpa.jefferson.edu/iSeqQC/">http://cancerwebpa.jefferson.edu/iSeqQC/</a></p>
<p><a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3399-8">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3399-8</a></p><p>Address of the bookmark: <a href="https://github.com/gkumar09/iSeqQC" rel="nofollow">https://github.com/gkumar09/iSeqQC</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</guid>
	<pubDate>Sun, 12 Apr 2020 10:02:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</link>
	<title><![CDATA[WEGO : simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results]]></title>
	<description><![CDATA[<p><span>WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary became more and more popular, WEGO was widely adopted and used in many researches. Therefore we have updated WEGO 2.0 in 2018. Here are some changes we&rsquo;ve made:</span><br><span>1. The limit of input file numbers was cancelled. Now the users could upload as many files as they want with one operation.</span><br><span>2. We have added the reference data of 9 species for users selection.</span><br><span>3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.</span></p><p>Address of the bookmark: <a href="http://wego.genomics.org.cn/" rel="nofollow">http://wego.genomics.org.cn/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42139/mixtures-a-novel-tool-for-bacterial-strain-reconstruction-from-reads</guid>
	<pubDate>Fri, 21 Aug 2020 08:23:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42139/mixtures-a-novel-tool-for-bacterial-strain-reconstruction-from-reads</link>
	<title><![CDATA[mixtureS: a novel tool for bacterial strain reconstruction from reads]]></title>
	<description><![CDATA[<div>
<p>mixtureS that can de novo identify bacterial strains from shotgun reads of a clonal or metagenomic sample, without prior knowledge about the strains and their variations. Tested on 243 simulated datasets and 195 experimental datasets, mixtureS reliably identified the strains, their numbers and their abundance. Compared with three tools, mixtureS showed better performance in almost all simulated datasets and the vast majority of experimental datasets.</p>
</div>
<div>
<div>Availability</div>
<p>The source code and tool mixtureS is available at&nbsp;<a href="http://www.cs.ucf.edu/~xiaoman/mixtureS/" target="_blank">http://www.cs.ucf.edu/&tilde;xiaoman/mixtureS/</a>.</p>
</div><p>Address of the bookmark: <a href="http://www.cs.ucf.edu/~xiaoman/mixtureS/" rel="nofollow">http://www.cs.ucf.edu/~xiaoman/mixtureS/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42362/magic-a-tool-for-predicting-transcription-factors-and-cofactors-driving-gene-sets-using-encode-data</guid>
	<pubDate>Thu, 26 Nov 2020 11:05:04 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42362/magic-a-tool-for-predicting-transcription-factors-and-cofactors-driving-gene-sets-using-encode-data</link>
	<title><![CDATA[MAGIC: A tool for predicting transcription factors and cofactors driving gene sets using ENCODE data]]></title>
	<description><![CDATA[<p><span>The algorithm presented herein,&nbsp;</span><strong>M</strong><span>ining&nbsp;</span><strong>A</strong><span>lgorithm for&nbsp;</span><strong>G</strong><span>enet</span><strong>I</strong><span>c&nbsp;</span><strong>C</strong><span>ontrollers (MAGIC), uses ENCODE ChIP-seq data to look for statistical enrichment of TFs and cofactors in gene bodies and flanking regions in gene lists without an&nbsp;</span><em>a priori</em><span>&nbsp;binary classification of genes as targets or non-targets. When compared to other TF mining resources, MAGIC displayed favourable performance in predicting TFs and cofactors that drive gene changes in 4 settings: </span></p>
<p><span>1) A cell line expressing or lacking single TF, </span></p>
<p><span>2) Breast tumors divided along PAM50 designations </span></p>
<p><span>3) Whole brain samples from WT mice or mice lacking a single TF in a particular neuronal subtype </span></p>
<p><span>4) Single cell RNAseq analysis of neurons divided by Immediate Early Gene expression levels. </span></p>
<p><span>In summary, MAGIC is a standalone application that produces meaningful predictions of TFs and cofactors in transcriptomic experiments.</span></p>
<p><span>More at&nbsp;https://uwmadison.app.box.com/s/8j90e5h2rjrsz3bacaxnq8kor2o64vyg</span></p><p>Address of the bookmark: <a href="https://github.com/asroopra/MAGIC" rel="nofollow">https://github.com/asroopra/MAGIC</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

</channel>
</rss>