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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29108?offset=820</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5187/bioinformatics-algorithms-part-1-with-pavel-pevzner-phillip-e-c-compeau</guid>
	<pubDate>Mon, 30 Sep 2013 11:34:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5187/bioinformatics-algorithms-part-1-with-pavel-pevzner-phillip-e-c-compeau</link>
	<title><![CDATA[Bioinformatics Algorithms (Part 1)  with Pavel  Pevzner, Phillip E. C. Compeau,]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/t5t_nfzdzEg" frameborder="0" allowfullscreen></iframe><p>The course Bioinformatics Algorithms (Part 1) by Pavel Pevzner, Phillip E. C. Compeau, and Nikolay Vyahhi from University of California, San Diego will be offered free of charge to everyone on the Coursera platform. Sign up at http://www.coursera.org/course/bioinformatics.</p>]]></description>
	
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5255/walk-in-interview-indian-agricultural-statistics-research-institute</guid>
  <pubDate>Wed, 02 Oct 2013 15:40:17 -0500</pubDate>
  <link></link>
  <title><![CDATA[Walk-in-Interview @ Indian Agricultural Statistics Research Institute]]></title>
  <description><![CDATA[
<p>Indian Agricultural Statistics Research Institute<br />Library Avenue, Pusa, New Delhi – 110012</p>

<p>Walk-in-Interview</p>

<p>Walk-in-interview will be held on October 5, 2013 at 10:00 A.M. at IASRI, New Delhi for a project “A New Distributed Computing Framework for Data Mining” funded by Department of Electronics and Information Technology, Government of India for the following posts. The appointment will be on contractual basis upto 14th October, 2015 or till the termination of the project whichever is earlier and the incumbent shall not have any claim for regular appointment under ICAR.</p>

<p>Research Associate</p>

<p>    Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or</p>

<p>    Post-Graduation in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 1st Division and at least two years of research experience</p>

<p>     Knowledge of Statistical Analysis /Bioinformatics tools for computational genomics.</p>

<p>     Knowledge of R/Perl programming language</p>

<p>Research Associate</p>

<p>    Ph.D. in Computer Science/ Computer Application / Bioinformatics/ Agricultural<br />    Statistics/ Statistics or equivalent or</p>

<p>    Post-Graduation in Computer Science/ Computer Application /Bioinformatics/ Agricultural Statistics/ Statistics or equivalent with 1st Division and at least two years of research experience</p>

<p>     Expertise in Java programming.<br />     Knowledge of system administration and networking under Linux environment.<br />     Knowledge of parallel programming and cluster computing.</p>

<p>Emoluments for Research Associate: Consolidated Rs:24000/- per month + HRA (for Ph.D. Degree holders) and Rs:23000/- per month + HRA (for Master’s Degree holders)</p>

<p>Age Limit: Age should be not more than 40 years (5 years relaxation for  SC/ST/women candidates and 3 years for OBC candidates as on date of interview).</p>

<p>Interested candidates are requested to appear for Walk-in-Interview on the date and time as specified above in Room No. 106, Training Cum Administrative Block of the Institute along with their application giving bio-data with attested copies of certificates, degrees, testimonials, etc. and one passport size photograph.</p>

<p>Original certificates/ Degrees are needed to be produced at the time of interview.</p>

<p>No T.A. /D.A. will be paid for appearing in the interview.</p>

<p>Advertisement: http://www.iasri.res.in/employment/employment.htm</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</guid>
	<pubDate>Wed, 29 Nov 2017 07:40:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</link>
	<title><![CDATA[Ribbon: Visualizing complex genome alignments and structural variation:]]></title>
	<description><![CDATA[<p>Ribbon can be used for long reads, short reads, paired-end reads, and assembly/genome alignments. Instructions for each data format are available by clicking on "instructions" in each tab on the right.</p>
<p>Local installation:</p>
<p>You can install Ribbon locally from Github by following the instructions here:&nbsp;<a href="https://github.com/MariaNattestad/ribbon" target="_blank">https://github.com/MariaNattestad/Ribbon</a></p><p>Address of the bookmark: <a href="http://genomeribbon.com/" rel="nofollow">http://genomeribbon.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5422/shendure-lab</guid>
  <pubDate>Wed, 09 Oct 2013 14:21:58 -0500</pubDate>
  <link></link>
  <title><![CDATA[Shendure Lab]]></title>
  <description><![CDATA[
<p>The Shendure Lab is part of the Department of Genome Sciences at the University of Washington (Seattle, WA). The mission of the lab is to develop and apply new technologies in genomics and molecular biology. Most projects in the lab exploit new DNA sequencing technologies (Shendure et al., Nature Reviews Genetics 2004; Shendure &amp; Ji, Nature Biotechnology 2008; Shendure &amp; Lieberman Aiden, Nature Biotechnology 2012), and generally fall into one of six areas: 1) next-generation human genetics; 2) genome contiguity &amp; completeness; 3) massively parallel functional analysis; 4) molecular tagging; 5) synthetic biology; 6) translational genomics. Our interests in each of these areas are outlined briefly below, and a full list of publications is available via PubMed. http://www.ncbi.nlm.nih.gov/pubmed?cmd=search&amp;term=shendure<br />More http://krishna.gs.washington.edu/research.html</p>

<p>Lab page @ http://krishna.gs.washington.edu/index.html</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34571/mugsy-multiple-whole-genome-alignment-tool</guid>
	<pubDate>Fri, 08 Dec 2017 17:41:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34571/mugsy-multiple-whole-genome-alignment-tool</link>
	<title><![CDATA[Mugsy: multiple whole genome alignment tool]]></title>
	<description><![CDATA[<p><span>Mugsy is a multiple whole genome aligner. Mugsy uses Nucmer for pairwise alignment, a custom graph based segmentation procedure for identifying collinear regions, and the segment-based progressive multiple alignment strategy from Seqan::TCoffee. Mugsy accepts draft genomes in the form of multi-FASTA files and does not require a reference genome.</span></p>
<p>To cite Mugsy, use:</p>
<p>Angiuoli SV and Salzberg SL.&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/27/3/334">Mugsy: Fast multiple alignment of closely related whole genomes.</a><em>Bioinformatics</em>&nbsp;2011 27(3):334-4</p><p>Address of the bookmark: <a href="http://mugsy.sourceforge.net/" rel="nofollow">http://mugsy.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5661/shankar-lab</guid>
  <pubDate>Wed, 16 Oct 2013 07:02:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Shankar Lab]]></title>
  <description><![CDATA[
<p>Research Interest:</p>

<p>(A) Regulatory System Analysis with respect to microRNAs</p>

<p>(B) Computational Epigenomics &amp; Regulomics:</p>

<p>(C) Computational issues with Next Generation Sequencing:</p>

<p>Department of Biotechnology, <br />Institute of Himalyan Bioresources Technology<br />CSIR, Palampur(Himachal Pradesh), India.<br />Email: ravishihbt.res.in; ravish9gmail.com</p>

<p>More @ http://scbb.ihbt.res.in/SCBB_dept/Lab_Member.php</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34867/magic-blast-a-tool-for-mapping-large-next-generation-rna-or-dna-sequencing-runs-against-a-whole-genome-or-transcriptome</guid>
	<pubDate>Tue, 26 Dec 2017 22:23:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34867/magic-blast-a-tool-for-mapping-large-next-generation-rna-or-dna-sequencing-runs-against-a-whole-genome-or-transcriptome</link>
	<title><![CDATA[Magic-BLAST: a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome.]]></title>
	<description><![CDATA[<p>Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.</p>
<p>Magic-BLAST incorporates within the NCBI BLAST code framework ideas developed in the NCBI Magic pipeline, in particular hit extensions by local walk and jump&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/26109056">(http://www.ncbi.nlm.nih.gov/pubmed/26109056)</a>, and recursive clipping of mismatches near the edges of the reads, which avoids accumulating artefactual mismatches near splice sites and is needed to distinguish short indels from substitutions near the edges.</p><p>Address of the bookmark: <a href="https://ncbi.github.io/magicblast/" rel="nofollow">https://ncbi.github.io/magicblast/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5747/dbbrowser-attwood-lab</guid>
  <pubDate>Fri, 18 Oct 2013 10:48:19 -0500</pubDate>
  <link></link>
  <title><![CDATA[DbBrowser: Attwood Lab]]></title>
  <description><![CDATA[
<p>DbBrowser: Attwood Lab research concerns protein sequence analysis, primarily using the method of protein 'fingerprinting'. DbBrowser: Attwood Lab maintain a diagnostic fingerprint database (PRINTS), one of the founding partner of InterPro. We also design software to display sequence and structural data in visually-striking ways (e.g., Ambrosia, CINEMA); DbBrowser: Attwood Lab are building re-usable software components to create semantically integrated bioinformatics applications through UTOPIA, including a 'smart' PDF reader that links bioinformatics databases and tools directly with scientific articles (Utopia Documents); and have developed a number of tools for automatic annotation and text mining (e.g., MINOTAUR, PRECIS, METIS). </p>

<p>More @ http://www.bioinf.manchester.ac.uk/dbbrowser/index.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41158/carefully-opt-for-human-reference-genome</guid>
	<pubDate>Tue, 18 Feb 2020 07:43:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41158/carefully-opt-for-human-reference-genome</link>
	<title><![CDATA[Carefully opt for human reference genome]]></title>
	<description><![CDATA[<p><a href="http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use" target="_blank">Heng Li posted several issues with the human reference genomes given in these resources</a> and suggests the following compressed FASTA file to be used as hg38/GRCh38 human reference genome.</p>
<p>if you map reads to GRCh38 or hg38, use the following:</p>
<div>
<div>
<pre><code>ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/001/405/GCA_000001405.15_GRCh38/seqs_for_alignment_pipelines.ucsc_ids/GCA_000001405.15_GRCh38_no_alt_analysis_set.fna.gz
</code></pre>
</div>
</div>
<p>There are several other versions of GRCh37/GRCh38. What&rsquo;s wrong with them? Here are a collection of potential issues:</p>
<p>More at http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use</p><p>Address of the bookmark: <a href="http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use" rel="nofollow">http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5946/bioinformatics-tata-memorial-centre-navi-mumbai</guid>
  <pubDate>Mon, 28 Oct 2013 10:40:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics @ TATA MEMORIAL CENTRE, NAVI MUMBAI]]></title>
  <description><![CDATA[
<p>TATA MEMORIAL CENTRE<br />ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER<br />KHARGHAR, NAVI MUMBAI – 410210</p>

<p>No. ACTREC/Advt./ 72 /2013</p>

<p>WALK IN INTERVIEW</p>

<p>1. JRF*<br />Genome-wide RNAi screen with human pooled tyrosine kinase shRNA libraries in head and neck squamous call carcinoma (HNSCC) cell lines<br />DBT A/C No. 3071, Dr. Amit Dutt</p>

<p>2. JRF<br />IRB Project ACTREC Funds<br />Dr. Amit Dutt</p>

<p>3. RA<br />Defining the cancer genome of Head and Neck Squamous Cell Carcinoma (HNSCC) with SNP arrays and next generation sequencing technology<br />A/C No. 2895, Dr. Amit Dutt</p>

<p>Duration of the Project: One year from the date of appointment, or as and when project terminates.</p>

<p>Consolidated Salary: RA : Rs. 40,000/- p.m.<br />JRF* (DBT): Rs. 20,800/- p.m.<br />JRF: Rs. 16,000/- p.m.<br />Date &amp; Time: 6th November, 2013, at 10.00 a.m.</p>

<p>Venue: Conference Room</p>

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

<p>RA: The ideal applicant should have a PhD in a relevant field. He/she should have a strong computational biology background, with demonstrated experience in coding using Perl, Python, Java or C++. He/she should be familiar with working in unix enviromnent, devising computational algorithms for data analysis, statistical data analysis in R and matlab and database programming using MySQL. Hands on experience in analyzing high throughput data would be an added advantage.</p>

<p>JRF* (DBT project): M.Sc. in Life Sciences or M.Tech in Biotechnology with good academic record (Minimum of 60% aggregate). Valid UGC-CSIR/DBT/ICMR JRF qualification and laboratory experience in molecular biology. Previous experience in molecular biology and animal tissue culture with high throughput platforms and ability to work with a large team would be desirable.</p>

<p>JRF (ACTREC project): M.Sc. in Life Sciences or M.Tech in Biotechnology with good academic record (Minimum of 60% aggregate). Minimum 2 yrs experience in molecular biology and animal tissue culture with high throughput platforms and ability to work with a large team is essential.</p>

<p>*M.Sc. degree obtained after a one year course will not be considered.</p>

<p>Candidates fulfilling above requirements should send their application by e-mail to<br />‘careers.duttlab@gmail.com. in the format given below so as to reach on or before<br />4th November, 2013.</p>

<p>Advertisement:</p>

<p>http://www.actrec.gov.in/data%20files/2013/AD-RA-JR-TECHN-6-NOV.pdf</p>
]]></description>
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