<?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/28141?offset=450</link>
	<atom:link href="https://bioinformaticsonline.com/related/28141?offset=450" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19137/centre-for-systems-biology-bioinformatics-panjab-university-vacancy-of-research-fellow</guid>
  <pubDate>Wed, 12 Nov 2014 06:18:54 -0600</pubDate>
  <link></link>
  <title><![CDATA[Centre for Systems Biology &amp; Bioinformatics, Panjab University vacancy of Research Fellow]]></title>
  <description><![CDATA[
<p>Applications are invited along with complete bio-data and attested copies of certificates of qualifications, experience etc. for the one post of <br />Research Fellow and one post of Program Assistant under PURSE Grant of the University in Centre for Systems Biology &amp; Bioinformatics, UIEAST, Panjab University, Chandigarh which is tenable till the period of the project</p>

<p>Essential Qualification<br />For Research Fellow:-<br />M.Sc. in Systems Biology and Bioinformatics / Life<br />Sciences with minimum 55% marks.<br />Preference will be given to NET/GATE/ICMR qualified candidates without fellowship however, candidates who have cleared the Panjab University Ph.D. entrance test in Systems Biology &amp; Bioinformatics will also be eligible. </p>

<p>Applications should be reach on or before 19-11-2014 in the office of the undersigned. Interview will be held on 21-11-2014 in the office of the Coordinator, Centre for Systems Biology &amp; Bioinformatics, South Campus, Block-3, Sector-25, Panjab University, Chandigarh. No TA/DA will be paid. </p>

<p>more at http://jobs.puchd.ac.in/includes/jobs/2014/20141110143634-Advertisement.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</guid>
	<pubDate>Tue, 08 May 2018 04:27:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</link>
	<title><![CDATA[HISAT2: a fast and sensitive alignment program for mapping next-generation sequencing reads]]></title>
	<description><![CDATA[<p><strong>HISAT2</strong><span>&nbsp;is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Based on an extension of BWT for graphs&nbsp;</span><a href="http://dl.acm.org/citation.cfm?id=2674828">[Sir&eacute;n et al. 2014]</a><span>, we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM).&nbsp;</span></p>
<p><span>more at&nbsp;https://ccb.jhu.edu/software/hisat2/index.shtml</span></p><p>Address of the bookmark: <a href="https://github.com/infphilo/hisat2" rel="nofollow">https://github.com/infphilo/hisat2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19248/bioinformatics-jrfrasrf-position-at-institute-of-cytology-and-preventive-oncology-icpo</guid>
  <pubDate>Wed, 19 Nov 2014 20:16:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/RA/SRF position at Institute of Cytology and Preventive Oncology (ICPO)]]></title>
  <description><![CDATA[
<p>Institute of Cytology and Preventive Oncology (ICPO) I-7, Sector-39, Noida-201301</p>

<p>Candidates having the below mentioned qualifications may appear for walk in interview at ICPO on 2nd December 2014 between 10.00 AM and 12:00 PM under the below time bound projects under Dr. Subhash M. Agarwal, Scientist C. The post is purely temporary and co-terminus with the project.</p>

<p>Research Assistant (One)<br />25650/- consolidated<br />Discovery of EGFR secondary mutant inhibitors using structure based screening approach (ICMR)<br />Duration: 7 months</p>

<p>Essential: M.Sc./ M.Tech in Bioinformatics or any other related subject with good academic record.</p>

<p>Desirable: Experience in scripting and molecular docking.<br />	<br />Below 30 years</p>

<p>Junior Research Fellow (One)</p>

<p>16,000 + 30% HRA = Rs. 20800/-</p>

<p>Identification of novel inhibitors targeting EGFR using an integrated ligand and structure based approach (DBT)</p>

<p>Duration: 9 months</p>

<p>Essential: M.Sc./ M.Tech in Bioinformatics or any other related subject with good academic record. Candidates with CSIR-UGC / ICMR, NET qualification will be preferred</p>

<p>Desirable: Experience in scripting, QSAR and molecular docking.<br />	<br />Below 28 years</p>

<p>Interested eligible candidates may send their applications with Bio-data by email at (smagarwal@gmail.com) or by post addressed to Dr. Subhash M Agarwal, Scientist C, Institute of Cytology and Preventive Oncology (ICPO) I-7, Sector-39, Noida-201301 so as to reach latest by 1st December, 2014. The candidates may appear for interview at ICPO along with 3 copies of CV, photo and relevant certificates of qualifications in original and reprints of publications at the time of interview. It should be noted that No TA/DA will be paid for the walk in Interview.</p>

<p>Advertisement: www.icpo.org.in/advt-walk-in-interview.docx</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37514/list-of-non-commercial-ngs-genotype-calling-software</guid>
	<pubDate>Thu, 09 Aug 2018 04:21:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37514/list-of-non-commercial-ngs-genotype-calling-software</link>
	<title><![CDATA[List of non-commercial NGS genotype-calling software]]></title>
	<description><![CDATA[<p><span>Meaningful analysis of next-generation sequencing (NGS) data, which are produced extensively by genetics and genomics studies, relies crucially on the accurate calling of SNPs and genotypes. Recently developed statistical methods both improve and quantify the considerable uncertainty associated with genotype calling, and will especially benefit the growing number of studies using low- to medium-coverage data.&nbsp;</span></p><p><span>A list of programs for genotype and SNP calling :</span></p><p><br />SOAP2&nbsp;http://soap.genomics.org.cn/index.html</p><p>Single-sample High-quality variant database (for example, dbSNP) Package for NGS data analysis, which includes a single individual genotype caller (SOAPsnp)</p><p>realSFS&nbsp;http://128.32.118.212/thorfinn/realSFS/</p><p>Single-sample Aligned reads Software for SNP and genotype calling using single individuals and allele frequencies. Site frequency spectrum (SFS) estimation</p><p>Samtools http://samtools.sourceforge.net/</p><p>Multi-sample Aligned reads Package for manipulation of NGS alignments, which includes a computation of genotype likelihoods (samtools) and SNP and genotype calling (bcftools)</p><p>GATK http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit Multi-sample Aligned reads Package for aligned NGS data analysis, which includes a SNP and genotype caller (Unifed Genotyper), SNP filtering (Variant Filtration) and SNP quality recalibration (Variant Recalibrator)</p><p>Beagle http://faculty.washington.edu/browning/beagle/beagle.html</p><p>Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation, phasing and association that includes a mode for genotype calling</p><p>IMPUTE2 http://mathgen.stats.ox.ac.uk/impute/impute_v2.html</p><p>Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation and phasing, including a mode for genotype calling. Requires fine-scale linkage map</p><p>QCall ftp://ftp.sanger.ac.uk/pub/rd/QCALL</p><p>Multi-sample LD &lsquo;Feasible&rsquo; genealogies at a dense set of loci, genotype likelihoods Software for SNP and genotype calling, including a method for generating candidate SNPs without LD information (NLDA) and a method for incorporating LD information (LDA). The &lsquo;feasible&rsquo; genealogies can be generated using Margarita (http://www.sanger.ac.uk/resources/software/margarita)</p><p>MaCH http://genome.sph.umich.edu/wiki/Thunder</p><p>Multi-sample LD Genotype likelihoods Software for SNP and genotype calling, including a method (GPT_Freq) for generating candidate SNPs without LD information and a method (thunder_glf_freq) for incorporating LD information</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19556/genome-origami</guid>
	<pubDate>Fri, 12 Dec 2014 22:48:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19556/genome-origami</link>
	<title><![CDATA[Genome Origami]]></title>
	<description><![CDATA[<p>There are several interesting factoid about our genomes, one of them is their folding. If we stretched out the DNA in a single cell, which is only a few millionths of an inch wide, it would span more than six feet. In other word, the size of six feet DNA fold themself to fit in a few millionths of an inch wide space. These DNA folding is a dynamic process that changes over time (!!). Researchers around the world have been trying to understand how DNA folds itself up so efficiently, and a recent post on the NIH Director&rsquo;s Blog highlights new research illustrating how the human genome folds inside the cell&rsquo;s nucleus, as well as how DNA folding affects gene regulation. The research team created this delightful video that demonstrates the principles involved using origami art.</p><p>http://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome<br /><br />Researchers have been working to determine how cells regulate gene expression for nearly as long as we&rsquo;ve known about DNA. How, for example, do nerve cells know to turn off only nerve cell genes and turn off bone cell genes? DNA folding loops are part of the answer. This research team, which published their findings in a paper in Cell http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4 , found that the number of loops is much lower than expected. There are only 10,000 loops instead of the predicted millions, and they form on/off switches in DNA.<br /><br /></p><p>More at http://www.eurekalert.org/pub_releases/2014-12/ru-3mr121114.php</p><p>Reference http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly</guid>
	<pubDate>Tue, 22 Jan 2019 09:39:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly</link>
	<title><![CDATA[List of tools frequently used while genome assembly]]></title>
	<description><![CDATA[<h4>List of tools frequently used while genome assembly:</h4><p>I have used the following assemblers</p><ul>
<li><a href="http://bioinf.spbau.ru/spades">Spades</a>&nbsp;(v. 3.10.1)</li>
<li><a href="http://canu.readthedocs.io/en/stable/index.html">CANU</a>&nbsp;(v. 1.6)</li>
<li><a href="https://github.com/rrwick/Unicycler">Unicycler&nbsp;</a>(v. v0.4.1)</li>
<li><a href="https://github.com/lh3/miniasm">Miniasm</a>&nbsp;(v. 0.2-r137-dirty)</li>
</ul><p>I have used the following mappers</p><ul>
<li><a href="https://github.com/lh3/minimap2">minimap2</a>&nbsp;(v.&nbsp;2.0rc1-r232)</li>
<li><a href="https://github.com/lh3/minimap">minimap&nbsp;</a>(v. 0.2-r124-dirty)</li>
<li><a href="https://github.com/lh3/bwa">bwa</a>&nbsp;(v.&nbsp;0.7.12-r1039)</li>
</ul><p>I have used the following polishing tools</p><ul>
<li><a href="https://github.com/isovic/racon">Racon</a>&nbsp;(v. not available)</li>
<li><a href="https://github.com/broadinstitute/pilon">Pilon</a>&nbsp;(v. 1.18)</li>
<li><a href="https://github.com/jts/nanopolish">Nanopolish</a>&nbsp;(v. 0.8.3)</li>
</ul><p>I have used the following tools to assess genome assembly characteristics</p><ul>
<li><a href="https://github.com/chjp/ANI">ANI.pl</a>&nbsp;(https://github.com/chjp/ANI)</li>
<li><a href="http://ecogenomics.github.io/CheckM/">CheckM</a>&nbsp;(v. 1.0.7)</li>
<li><a href="https://github.com/tseemann/prokka">Prokka</a>&nbsp;(v. 1.12)</li>
<li><a href="http://bioinf.spbau.ru/en/quast">QUAST</a>&nbsp;(v. 2.3)</li>
<li><a href="http://mummer.sourceforge.net/">mummer&nbsp;</a>(v. not available)</li>
</ul><p>If you have any ideas or superior tools we have missed please let us know in the comments.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19545/walk-%E2%80%93-in-%E2%80%93-interview-agricultural-knowledge-management-unit-indian-agricultural-research-institute-new-delhi-110012</guid>
  <pubDate>Fri, 12 Dec 2014 21:33:02 -0600</pubDate>
  <link></link>
  <title><![CDATA[WALK – IN – INTERVIEW @ Agricultural Knowledge Management Unit Indian Agricultural Research Institute, New Delhi-110012]]></title>
  <description><![CDATA[
<p>Walk-in-interview for the following temporary positions will be conducted on 20th December 2014 (between 10:00 AM to 01:00 PM) at Agricultural Knowledge Management Unit, A0 block (Ground Floor), LBS Building, Indian Agricultural Research Institute, New Delhi-110012:</p>

<p>1 Dr. A.K.Mishra Coordinator &amp; PI (BTISnet)</p>

<p>Traineeship (two) for one year</p>

<p>Rs. 5000/- (consolidated)</p>

<p>M.Sc. (Bioinformatics) with 60 % marks from a recognized University</p>

<p>20-12-2014 (10:00 AM -11:00 AM)</p>

<p>Studentship (four) for one year</p>

<p>Rs. 2500/- (consolidated)</p>

<p>Final year M.Sc./ M.Tech (Bioinformatics) Students from a recognized University</p>

<p>20-12-2014 (11:00 AM- 1:00 PM)</p>

<p>The positions are purely temporary and co-terminus with the DBT Programme. Eligible candidates are requested to submit the application form in the prescribed format along with original certificates/ documents (Degree, Marks sheets, Work experience, if any) at the time of interview. No TA/DA will be paid. Maximum age limit is 28 years for all positions. Age relaxation of 5 yrs for SC/ST and woman candidates and 3 years for OBC candidates will be given. Canvassing in any form invites disqualification.</p>

<p>Advertisement: http://www.iari.res.in/files/BIC-08122014-20141208-172344.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</guid>
	<pubDate>Thu, 23 Jul 2020 05:49:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</link>
	<title><![CDATA[wgd—simple command line tools for the analysis of ancient whole-genome duplications]]></title>
	<description><![CDATA[<p><span>wgd is a easy to use command-line tool for<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>distribution construction named wgd. The wgd suite provides commonly used<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>and colinearity analysis workflows together with tools for modeling and visualization, rendering these analyses accessible to genomics researchers in a convenient manner.</span></p>
<p><a href="https://academic.oup.com/bioinformatics/article/35/12/2153/5162749">https://academic.oup.com/bioinformatics/article/35/12/2153/5162749</a></p><p>Address of the bookmark: <a href="https://github.com/arzwa/wgd" rel="nofollow">https://github.com/arzwa/wgd</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics</guid>
	<pubDate>Thu, 18 Dec 2014 11:05:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics</link>
	<title><![CDATA[Google Genomics]]></title>
	<description><![CDATA[<ul>
<li>
<p><strong>Explore genetic variation interactively.</strong> Compare entire cohorts in seconds with SQL-like queries. Compute transition/transversion ratios, genome-wide association, allelic frequency and more.</p>
</li>
<li>
<p><strong>Process big genomic data easily.</strong> Run batch analyses like principal component analysis and Hardy-Weinberg equilibrium on as many samples as you like, in minutes or hours, with just a little code.</p>
</li>
<li>
<p><strong>Use Google's infrastructure and big data expertise.</strong> Store one genome or a million using Google Genomics and take advantage of the same infrastructure that powers Search, Maps, YouTube, Gmail and Drive.</p>
</li>
<li>
<p><strong>Support emerging global standards.</strong> Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.</p>
</li>
</ul><p>Address of the bookmark: <a href="https://cloud.google.com/genomics/" rel="nofollow">https://cloud.google.com/genomics/</a></p>]]></description>
	<dc:creator>Tenzin Paul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43260/bioinformatics-tools-for-telomere-to-telomere-assembly</guid>
	<pubDate>Tue, 17 Aug 2021 13:17:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43260/bioinformatics-tools-for-telomere-to-telomere-assembly</link>
	<title><![CDATA[Bioinformatics tools for telomere to telomere assembly !]]></title>
	<description><![CDATA[<p>●&nbsp;<a href="https://github.com/arangrhie/merfin" target="_blank">Merfin</a>&nbsp;&ndash; k-mer-based assembly and variant calling evaluation for improved consensus accuracy (Arang Rhie)<br />●&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.11.11.378133v1" target="_blank">PanGenie</a>&nbsp;&ndash; algorithm that leverages a pangenome reference built from haplotype-resolved genome assemblies in conjunction with k-mer count information from raw, short-read sequencing data to genotype a wide spectrum of genetic variation (Tobias Marschall)<br />●&nbsp;<a href="https://github.com/ConesaLab/SQANTI3" target="_blank">SQANTI3</a>&nbsp;&ndash; an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline (Roc&iacute;o Amor&iacute;n de Heged&uuml;s&nbsp;<a href="https://twitter.com/rocioadh" target="_blank">@rocioadh</a>)<br />●&nbsp;<a href="https://github.com/GenomeRIK/tama" target="_blank">tama</a>&nbsp;(Transcriptome Annotation by Modular Algorithms) &ndash; software designed for processing Iso-Seq data and other long-read transcriptome data (Richard Kuo&nbsp;<a href="https://twitter.com/GenomeRIK" target="_blank">@GenomeRIK</a>)<br />●&nbsp;<a href="https://github.com/PacificBiosciences/pbAA" target="_blank">pbaa</a>&nbsp;(PacBio Amplicon Analysis) &ndash; separates complex mixtures of amplicon targets from genomic samples to cluster and generate high-quality consensus sequences from HiFi reads (Zev Kronenberg&nbsp;<a href="https://twitter.com/zevkronenberg" target="_blank">@zevkronenberg</a>)<br />●&nbsp;<a href="https://github.com/yuanyuan929/bellerophon" target="_blank">bellerophon</a>&nbsp;&ndash; analyzes MHC typing and other low-complexity gene amplicon data; performs allele calling while detecting polymorphic sites within the sequences and removing potential chimeric sequence variants (Yuanyuan Cheng&nbsp;<a href="https://twitter.com/Yuanyuan929" target="_blank">@Yuanyuan929</a>)<br />●&nbsp;<a href="https://github.com/amwenger/svpack" target="_blank">svpack</a>&nbsp;&ndash; tools for filtering, comparing, and annotating structural variant (SV) calls in VCF format (Aaron Wenger)<br />●&nbsp;<a href="https://github.com/AntonBankevich/jumboDB" target="_blank">JumboDB</a>&nbsp;&ndash; tool for de Bruijn graph construction (Anton Bankevich&nbsp;<a href="https://twitter.com/AntonBankevich" target="_blank">@AntonBankevich</a>)<br />●&nbsp;<a href="https://github.com/ksahlin/ultra" target="_blank">uLTRA</a>&nbsp;&ndash; tool for splice alignment of long transcriptomic reads to a genome, guided by a database of exon annotations. (Kristoffer Sahlin&nbsp;<a href="https://twitter.com/krsahlin" target="_blank">@krsahlin</a>)<br />●&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2021.01.25.428044v1.full.pdf" target="_blank">LeafGo</a>&nbsp;&ndash; workflow to rapidly produce high-quality de novo plant genomes (Luca Ermini&nbsp;<a href="https://twitter.com/ermini_luca" target="_blank">@ermini_luca</a>)</p><p>Reference:</p><p>https://www.pacb.com/blog/young-investigators-share-stellar-science-career-advice-and-bioinformatics-tools-at-smrt-leiden-2021/</p><p>&nbsp;</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

</channel>
</rss>