<?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/27099?offset=940</link>
	<atom:link href="https://bioinformaticsonline.com/related/27099?offset=940" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:39:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data</link>
	<title><![CDATA[SeqMonk:A tool to visualise and analyse high throughput mapped sequence data]]></title>
	<description><![CDATA[<p>SeqMonk is a program to enable the visualisation and analysis of mapped sequence data. It was written for use with mapped next generation sequence data but can in theory be used for any dataset which can be expressed as a series of genomic positions. It's main features are:</p>
<ul>
<li>Import of mapped data from mapped data (BAM/SAM/bowtie etc)</li>
<li>Creation of data groups for visualisation and analysis</li>
<li>Visualisation of mapped regions against an annotated genome.</li>
<li>Flexible quantitation of the mapped data to allow comparisons between data sets</li>
<li>Statistical analysis of data to find regions of interest</li>
<li>Creation of reports containing data and genome annotation</li>
</ul><p>Address of the bookmark: <a href="http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/" rel="nofollow">http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20271/research-associate-tata-memorial-centre-advanced-centre-for-treatment-research-and-education-in-cancer-kharghar-navi-mumbai</guid>
  <pubDate>Thu, 08 Jan 2015 20:53:57 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Associate	@ TATA MEMORIAL CENTRE ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER KHARGHAR, NAVI MUMBAI]]></title>
  <description><![CDATA[
<p>TATA MEMORIAL CENTRE ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER KHARGHAR, NAVI MUMBAI – 410210</p>

<p>Website: www.actrec.gov.in; Ph: 27405000</p>

<p>No. ACTREC/Advt./ 66 /2014 23rd December, 2014<br />Research Associate	</p>

<p>International Cancer Genome Consortium (ICGC) - India Project (IRB Project No. 3 A/c. No. 2408)</p>

<p>Dr. Rajiv Sarin</p>

<p>Duration of the Project: One year Extendable up to Three years.</p>

<p>Consolidated Salary: Rs. 42,000/- p.m.</p>

<p>Application last date: 8th January, 2015.</p>

<p>Interview Date &amp; Time: 21st January, 2015, at 11.00 a.m.</p>

<p>Venue: Conference Room, 3rd floor, Khanolkar Shodhika, ACTREC.</p>

<p>Essential Qualifications and Experience:</p>

<p>Ph.D (any branch of Life Sciences)</p>

<p>The candidate must have at least one year experience after Ph.D., preferably in Genomics and Molecular Biology.</p>

<p>Candidates fulfilling these requirements should pre register themselves by sending their application in the prescribed format with recent CV and contact details of 2 referees by e-mail to icgc@actrec.gov.in latest 8th January, 2015 by 10.00 a.m.</p>

<p>Candidates shortlisted for the interview will be intimated by email on or before 9th January, 2015.</p>

<p>The interviews would be held on 21st January 2015 and will be only for the pre registered candidates who have been shortlisted.<br />No T.A./D.A. will be admissible for attending the interview.</p>

<p>At the time of Interview the candidate should bring original certificates along with CV with contact details of 2 referees and submit the photocopies (attested) of the certificates, with a recent passport size photograph.</p>

<p>Advertisement: www.actrec.gov.in/data%20files/2014/Walk-in-Research-Fellow-26-12-14.doc</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</guid>
	<pubDate>Thu, 04 Oct 2018 16:39:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37837/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>This is a tool for detecting structural variations using soft-clipping information From&nbsp;<a href="http://samtools.sourceforge.net/SAM1.pdf">SAM</a>&nbsp;files.</p>
<p>https://github.com/shinout/clipcrop</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>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/20454/comparative-genomics-in-ensembl</guid>
	<pubDate>Wed, 21 Jan 2015 08:31:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/20454/comparative-genomics-in-ensembl</link>
	<title><![CDATA[Comparative Genomics in Ensembl]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/dDRdCnZOMCM" frameborder="0" allowfullscreen></iframe>The Ensembl browser provides viewable whole-genome alignments, homologues and phylogenetic gene trees, protein families, and ancestral sequences.  Learn how to view and export these data in this video.]]></description>
	
</item>
<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/bookmarks/view/20471/bioinformatics-scripts</guid>
	<pubDate>Thu, 22 Jan 2015 22:29:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/20471/bioinformatics-scripts</link>
	<title><![CDATA[Bioinformatics Scripts]]></title>
	<description><![CDATA[<p>Some of the useful bioinformatics scripts.</p>
<p>For example ... contig-stats.pl is a Perl script that will automatically describe features of a sequence assembly.</p>
<p>http://milkweedgenome.org/?q=scripts</p><p>Address of the bookmark: <a href="http://milkweedgenome.org/?q=scripts" rel="nofollow">http://milkweedgenome.org/?q=scripts</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40359/minipolish-a-tool-for-racon-polishing-of-miniasm-assemblies</guid>
	<pubDate>Tue, 03 Dec 2019 02:40:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40359/minipolish-a-tool-for-racon-polishing-of-miniasm-assemblies</link>
	<title><![CDATA[Minipolish: A tool for Racon polishing of miniasm assemblies]]></title>
	<description><![CDATA[<p><a href="https://github.com/lh3/miniasm">Miniasm</a>&nbsp;is a great long-read assembly tool: straight-forward, effective and very fast. However, it does not include a polishing step, so its assemblies have a high error rate &ndash; they are essentially made of stitched-together pieces of long reads.</p>
<p><a href="https://github.com/isovic/racon">Racon</a>&nbsp;is a great polishing tool that can be used to clean up assembly errors. It's also very fast and well suited for long-read data. However, it operates on FASTA files, not the&nbsp;<a href="https://github.com/GFA-spec/GFA-spec/blob/master/GFA1.md">GFA graphs</a>&nbsp;that miniasm makes.</p>
<p>That's where Minipolish comes in. With a single command, it will use Racon to polish up a miniasm assembly, while keeping the assembly in graph form.</p>
<p>It also takes care of some of the other nuances of polishing a miniasm assembly:</p>
<ul>
<li>Adding read depth information to contigs</li>
<li>Fixing sequence truncation that can occur in Racon</li>
<li>Adding circularising links to circular contigs if not already present (so they display better in&nbsp;<a href="https://github.com/rrwick/Bandage">Bandage</a>)</li>
<li>'Rotating' circular contigs between polishing rounds to ensure clean circularisation</li>
</ul><p>Address of the bookmark: <a href="https://github.com/rrwick/Minipolish" rel="nofollow">https://github.com/rrwick/Minipolish</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/20504/chromevol</guid>
	<pubDate>Sun, 25 Jan 2015 00:33:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/20504/chromevol</link>
	<title><![CDATA[ChromEvol]]></title>
	<description><![CDATA[<p>Chromosome number is a remarkably dynamic feature of eukaryotic evolution. Chromosome numbers can change by a duplication of the whole genome (a process termed polyploidy), or by single chromosome changes (ascending dysploidy via, e.g., chromosome fission or descending dysploidy via, e.g., chromosome fusion).<br> Of the various mechanisms of chromosome number change, polyploidy has received significant attention because of the impact such an event may have on the organism.<br> ChromEvol implements a series of likelihood models for the evolution of chromosome numbers. By comparing the fit of the different models to biological data, it may be possible to gain insight regarding the pathways by which the evolution of chromosome number proceeds. For each model, the program estimates the rates for the possible transitions assumed by the model, infers the set of ancestral chromosome numbers, and estimates the location along the tree for which polyploidy events (and other chromosome number changes) occurred. For further methodological details, see the publications and manual on the Downloads page.</p>
<p>http://www.tau.ac.il/~itaymay/cp/chromEvol/about.html</p><p>Address of the bookmark: <a href="http://www.tau.ac.il/~itaymay/cp/chromEvol/downloads.html" rel="nofollow">http://www.tau.ac.il/~itaymay/cp/chromEvol/downloads.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads</guid>
	<pubDate>Fri, 31 Jan 2020 05:50:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads</link>
	<title><![CDATA[HASLR: a tool for rapid genome assembly of long sequencing reads]]></title>
	<description><![CDATA[<p><span>HASLR is a tool for rapid genome assembly of long sequencing reads. HASLR is a hybrid tool which means it requires long reads generated by Third Generation Sequencing technologies (such as PacBio or Oxford Nanopore) together with Next Generation Sequencing reads (such as Illumina) from the same sample.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/haslr" rel="nofollow">https://github.com/vpc-ccg/haslr</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20672/jrfra-structuralcomputational-biology-at-icgeb</guid>
  <pubDate>Thu, 29 Jan 2015 11:52:40 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF/RA Structural/Computational Biology at ICGEB]]></title>
  <description><![CDATA[
<p>Research Associate and JRF positions in the Structural and Computational Biology Group starting 1st March 2015. Collaborative projects include work on:</p>

<p>a) bioinformatics, systems and computational biology <br />b) malaria <br />c) drug discovery <br />d) genomics <br />e) microbiology <br />f) metabolic disorders <br />g) molecular medicine</p>

<p>Eligibility: Applicants must have one of the following :</p>

<p>1) INSPIRE award for undertakig either PhD or Postdoctoral research; <br />2) SPM award for PhD; <br />3) JRF for pursuing PhD from CSIR/DBT/ICMR</p>

<p>Interest and experience in Biochemistry/Bioinformatics/Biophysics/ Chemistry/Genomics/Molecular Biology/ is essential.</p>

<p>Submit curriculum vitae to sb.icgeb@gmail.com by 20 February 2015</p>
]]></description>
</item>

</channel>
</rss>