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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30111?offset=970</link>
	<atom:link href="https://bioinformaticsonline.com/related/30111?offset=970" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</guid>
	<pubDate>Fri, 19 Oct 2018 07:25:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</link>
	<title><![CDATA[BASE: a practical de novo assembler for large genomes using long NGS reads]]></title>
	<description><![CDATA[<p><span>new&nbsp;</span><em>de novo</em><span>&nbsp;assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.</span></p><p>Address of the bookmark: <a href="https://github.com/dhlbh/BASE" rel="nofollow">https://github.com/dhlbh/BASE</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/23912/jrf-in-bioinformatics-central-university-of-rajasthan</guid>
  <pubDate>Thu, 20 Aug 2015 05:28:21 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF in Bioinformatics @ Central University of Rajasthan]]></title>
  <description><![CDATA[
<p>Central University of Rajasthan<br />Department of Biotechnology<br />School of Life Sciences<br />Bandarsindri, Distt. Ajmer</p>

<p>Applications are invited for one JRF position supported by DST sponsored project in Bioinformatics with Dr. Tarun Kumar Bhatt.</p>

<p>Title of the project: Molecular Modeling of malaria parasite ‘secretome’: A potential drug target</p>

<p>Fellowship: Rs. 14000 consolidated</p>

<p>Duration of project: 36 months.</p>

<p>Essential Qualification: Master’s degree in Biotechnology/Bioinformatics with minimum 55% marks. Age limit as per government rule.</p>

<p>Candidates with good experience of molecular modeling, In-silico screening, MD simulation and database formation will be preferred. Good knowledge of Linux operating system is desirable.</p>

<p>How to apply: Interested candidate can send soft copy of application in format given below to tarun@curaj.ac.in on or before 29/08/2015.</p>

<p>1. Name<br />2. Fathers name<br />3. Date of Birth<br />5. Age<br />6. Sex<br />7. Address<br />8. Telephone / mobile no.<br />9. Email:<br />10. Academic qualifications starting from 10th class.<br />11. Summary of experience in molecular modeling, In-silico screening and database formation.</p>

<p>General Conditions:</p>

<p>1.Selected candidate would be informed for date and time of the interview via email .<br />2. No TA/DA will be paid for attending the interview.</p>

<p>More at http://www.curaj.ac.in/2015/Rec/aug/Advertisement%20for%20post%20of%20JRF%20under%20DST%20project%28BioTech%29.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38829/nquire-a-statistical-framework-for-ploidy-estimation-using-ngs-short-read-data</guid>
	<pubDate>Thu, 31 Jan 2019 05:12:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38829/nquire-a-statistical-framework-for-ploidy-estimation-using-ngs-short-read-data</link>
	<title><![CDATA[nQuire: A statistical framework for ploidy estimation using NGS short-read data]]></title>
	<description><![CDATA[<p>nQuire implements a set of commands to estimate ploidy level of individuals from species, where recent polyploidization occurred and intraspecific ploidy variation is observed. Specifically, nQuire uses next-generation sequencing data to distinguish between diploids, triploids and tetraploids, on the basis of frequency distributions at variant sites where only two bases are segregating.</p>
<p>For more background see also the publication at&nbsp;<a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2128-z">BMC Bioinformatics</a>.</p>
<p>https://github.com/clwgg/nQuire</p><p>Address of the bookmark: <a href="https://github.com/clwgg/nQuire" rel="nofollow">https://github.com/clwgg/nQuire</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24074/bioinformatics-training-fellowship</guid>
  <pubDate>Fri, 28 Aug 2015 16:02:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Training Fellowship !!]]></title>
  <description><![CDATA[
<p>Applications are invited from suitable candidates for six months ‘Training Fellowship’ in Bioinformatics under the BTISNET program of DBT in the Distributed Information Sub center (DISC) facility at NIPGR, New Delhi, under the supervision of Dr. Gitanjali Yadav, Scientist, NIPGR.</p>

<p>Project Title 	No. of post(s) 	Designation 	Stipend in  	Tenure 	Start 	End<br />Establishment of Distributed Information Sub-Centre (DISC) 	02 	Trainee Fellow / Student Fellow 	5,000/- p.m 	Six months 	01/01/2016 	30/06/2016</p>

<p>Essential Qualification: </p>

<p>Traineeship: Candidate having B.Tech or Master Degree or equivalent in Bioinformatics/ Biotechnology with strong interest in Computational Biology and First class/ division throughout academic career may apply. </p>

<p>Studentship: Students currently pursuing the final year of B.Tech or Masters Degree or equivalent in Bioinformatics/ Biotechnology, requiring a thesis as a necessary pre-requisite for completion of respective degree and First class/ division throughout academic career may apply.</p>

<p>Desirable Qualification: Proficiency in Coding Algorithms and Bioinformatics Applications, evidenced by short trainings or computing courses.</p>

<p>The positions are purely temporary and co-terminus with the tenure of the training period as mentioned above. NIPGR reserves the right to select the candidate against the above fellowship depending upon the qualification and experience of the candidate. Reservations shall be as per Govt. of India norms. The applicants will have no claim implicit or explicit for consideration against any regular position of DISC/NIPGR.</p>

<p>Eligible candidates may apply online application form available</p>

<p>at http://www.nipgr.res.in/discform.html within 15 days from the date of</p>

<p>advertisement.Applications received through any other mode will be disqualified outright. </p>

<p>More at http://www.nipgr.res.in/discform.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40546/clincnv-detection-of-copy-number-changes-in-germlinetriosomatic-contexts-in-ngs-data</guid>
	<pubDate>Thu, 16 Jan 2020 23:16:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40546/clincnv-detection-of-copy-number-changes-in-germlinetriosomatic-contexts-in-ngs-data</link>
	<title><![CDATA[ClinCNV: Detection of copy number changes in Germline/Trio/Somatic contexts in NGS data]]></title>
	<description><![CDATA[<p><span>ClinCNV detects CNVs in germline and somatic context in NGS data (targeted and whole-genome). We work in cohorts, so it makes sense to try&nbsp;</span><code>ClinCNV</code><span>&nbsp;if you have more than 10 samples (recommended amount - 40 since we estimate variances from the data). By "cohort" we mean samples sequenced with the same enrichment kit with approximately the same depth (ie 1x WGS and 30x WGS better be analysed in separate runs of ClinCNV). Of course it is better if your samples were sequenced within the same sequencing facility.</span></p><p>Address of the bookmark: <a href="https://github.com/imgag/ClinCNV" rel="nofollow">https://github.com/imgag/ClinCNV</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24364/ra-bioinformatics-at-university-of-delhi</guid>
  <pubDate>Thu, 10 Sep 2015 16:02:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at University of Delhi]]></title>
  <description><![CDATA[
<p>BIOINFORMATICS INFRASTRUCTURE FACILITY</p>

<p>GARGI COLLEGE (University of Delhi)</p>

<p>SiriFort Road, New Delhi-110049</p>

<p>Walk- in- interview Bioinformatics Infrastructure Facility (BIF), Gargi College, University of Delhi invites to appear for interview on 29th September, 2015 at 9.30 AM for filling up the following purely temporary position sponsored by DBT, New Delhi.</p>

<p>1. Traineeship – 01 (one post) purely temporary for a period of six months.</p>

<p>Salary: Rs.8000/- p.m. fixed.</p>

<p>Essential Qualification: Post Graduate degree in Bioinformatics or any other branch of Life Sciences preferably with dissertation in Bioinformatics.</p>

<p>Desirable Qualification: Prior knowledge of programming languages such as C, VB, SQL etc. and software/database development.</p>

<p>2. Research Associate-01(one post) purely temporary for a period of nine months.</p>

<p>Salary: Rs 36000/-+HRA p.m fixed.</p>

<p>Essential Qualification: PhD in Bioinformatics/Biological Sciences/Computer Science or allied sciences with proven experience in bioinformatics.</p>

<p>3. Studentship- 01 (one post) purely temporary for a period of six months.</p>

<p>Salary: Rs.8000/- p.m. fixed.</p>

<p>Essential Qualifications: Final year Post Graduate students pursuing a degree in Bioinformatics or any branch of Life Science with knowledge of bioinformatics.</p>

<p>Interested candidates are required to appear for the walk in interview on 29th September, 2015 at 9.30 AM in Principal’s Office, Gargi College, Sirifort Road, N. Delhi-110049, with their CVs, original documents and a set of Photostat copies of all original documents. Conditions: The original documents must be produced at the time of interview, otherwise will not be allowed to attend the same. No TA &amp; DA will be paid for appearing in the interview. The institute reserves the right to fill or not to fill the positions depending upon qualifications/credentials of the candidates etc. The appointment does not confer any right over the job and will not be considered as institute’s service. Dr Aparajita Mohanty Dr Shashi Tyagi (Co-coordinator,BIF) (Coordinator, BIF)</p>

<p>Advertisement:</p>

<p>http://gargi.du.ac.in/uploads/ngrey/News/Gargi_Advt_BIF_2015.pdf</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42917/fings-filters-for-next-generation-sequencing</guid>
	<pubDate>Sat, 27 Feb 2021 01:18:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42917/fings-filters-for-next-generation-sequencing</link>
	<title><![CDATA[FiNGS: Filters for Next Generation Sequencing]]></title>
	<description><![CDATA[<h2>Key features</h2>
<ul>
<li><strong>Filters SNVs from any variant caller to remove false positives</strong></li>
<li><strong>Calculates metrics based on BAM files and provides filtering not possible with other tools</strong></li>
<li><strong>Fully user-configurable filtering (including which filters to use and their thresholds)</strong></li>
<li><strong>Option to use filters identical to ICGC recommendations</strong></li>
</ul>
<p>FiNGS provides researchers with a tool to reproducibly filter somatic variants that is simple to both deploy and use, with filters and thresholds that are fully configurable by the user. It ingests and emits standard variant call format (VCF) files and will slot into existing sequencing pipelines. It allows users to develop and implement their own filtering strategies and simple sharing of these with others.</p>
<p>FiNGS reliably improves upon the precision of default variant caller outputs and performs better than other tools designed for the same task.</p><p>Address of the bookmark: <a href="https://github.com/cpwardell/FiNGS" rel="nofollow">https://github.com/cpwardell/FiNGS</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24665/national-research-centre-on-plant-biotechnology-for-rajrf-positions</guid>
  <pubDate>Sat, 26 Sep 2015 20:32:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[National Research Centre on Plant Biotechnology for RA/JRF positions]]></title>
  <description><![CDATA[
<p>National Research Centre on Plant Biotechnology - New Delhi, Delhi<br />National Research Centre on Plant Biotechnology recruitments job vacancies for RA/JRF positions</p>

<p>Name of post: Research Associate<br />Salary: Rs.36000/-+ 30% HRA*<br />Educational Qualification: Candidates should have PhD in Biotechnology / Bioinformatics Life Sciences (or) M.Sc Biotechnology / Bioinformatics with three years research experience in relevant field</p>

<p>Name of post: Junior Research Fellow<br />Salary: Rs.25000/-+ 30% HRA*<br />Educational Qualification: Candidates should have M.Sc in Biotechnology /Bioinformatics / Life Sciences with 1st Division or 60% marks or equivalent overall grade point from any recognized professional University</p>

<p>Age Limit: 35 years max. (5 years relaxation for SC/ST/OBC)</p>

<p>How to attend walk in interview?<br />Interested candidates may attend Walk- in-interview on 1st October, 2015 at 10 am at NRCPB, LBS Building, Pusa Campus, and New Delhi-110012 at the above address along with updated Bio-data (CV), ID Proof &amp; attested copies of Certificates and Original to prove qualification &amp; Experience.</p>

<p>Recruitment reference: http://www.nrcpb.org/jobslist</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44672/libraries-or-management-tools-for-high-throughput-sequencing-data</guid>
	<pubDate>Fri, 04 Oct 2024 02:45:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44672/libraries-or-management-tools-for-high-throughput-sequencing-data</link>
	<title><![CDATA[Libraries or management tools for high throughput sequencing data]]></title>
	<description><![CDATA[<ul>
<li><a href="http://gatb.inria.fr/"><span>GATB</span></a>&nbsp;Library.&nbsp;The&nbsp;<span>Genome Analysis Toolbox with de-Bruijn graph.&nbsp;</span>A large part of tools developed by the GenScale team are based on this library.<br />These methods enable the analysis of data sets of any size on multi-core desktop computers, including very huge amount of reads data coming from any kind of organisms such as bacteria, plants, animals and even complex samples (<em>e.g.</em>&nbsp;metagenomes). Among them are (the full is available here:&nbsp;<a href="https://gatb.inria.fr/software/">https://gatb.inria.fr/software/</a>):</li>
<li><a href="https://github.com/morispi/LRez"><span>LRez</span></a>: C++ Library and toolkit for the barcode-based management and indexation of linked-read datasets.</li>
</ul><h2>Variant calling and/or genotyping</h2><ul>
<li><a href="https://gatb.inria.fr/software/discosnp/" title="DiscoSNP">DiscoSNP++ and&nbsp;discoSnpRAD</a>: Reference-free small variant discovery (SNPs and indels)</li>
<li><a href="https://gatb.inria.fr/software/mind-the-gap/" title="MindTheGap">MindTheGap</a>: Detection and assembly of large insertion variants</li>
<li><a href="https://gatb.inria.fr/software/takeabreak/" title="TakeABreak">TakeABreak</a>:&nbsp;reference-free inversion discovery tool</li>
<li><a href="https://github.com/llecompte/SVJedi">SVJedi</a>: Structural Variant genotyper with long read data</li>
<li><a href="https://github.com/SandraLouise/SVJedi-graph">SVJedi-graph</a>: Structural Variant genotyper with long read data using a variation graph</li>
</ul><h2>Sequence assembly</h2><ul>
<li><a href="https://github.com/cguyomar/MinYS">MinYS</a>: reference-guided genome assembly in metagenomics data</li>
<li><a href="https://github.com/anne-gcd/MTG-Link">MTG-link</a>: local assembly tool for linked-read data</li>
<li><a href="https://gatb.inria.fr/software/minia/" title="Minia">Minia</a>: De novo short read assembler</li>
<li><a href="https://gatb.inria.fr/de-novo-genome-assembly/">de-novo pipeline</a>:&nbsp;<em>de-novo</em>&nbsp;assembly pipeline (error correction / contigs / scaffolding) for genomes and meta-genomes</li>
<li><a href="https://gatb.inria.fr/software/mapsembler/" title="Mapsembler2">Mapsembler2</a>: Targeted assembly (not maintained)</li>
</ul><h2>Managing k-mers &amp; indexation</h2><ul>
<li><a href="https://github.com/lrobidou/findere">findere</a>:&nbsp;simple strategy for speeding up queries and for reducing false positive calls from any Approximate Membership Query data structure.
<ul>
<li><a href="https://github.com/lrobidou/fimpera">fimpera</a>&nbsp;extends findere adding the abundance information.</li>
</ul>
</li>
<li><a href="https://github.com/tlemane/kmtricks">kmtricks</a>:&nbsp;modular tool suite for counting kmers, and constructing Bloom filters or kmer matrices, for large collections of sequencing data.</li>
<li><a href="https://github.com/tlemane/kmindex">kmindex&nbsp;</a>is a tool for indexing and querying sequencing samples. It is built on top of kmtricks.</li>
<li><a href="https://github.com/pierrepeterlongo/back_to_sequences">back to sequences</a>: Find sequences (reads, unitigs, genes) related to a set of kmers in large datasets, in a matter of seconds.</li>
<li><a href="https://github.com/vicLeva/bqf">Backpack Quotient Filter</a>:&nbsp;k-mer indexing data structure with abundance</li>
<li><a href="http://github.com/GATB/rconnector">short read connector</a>:&nbsp;Detect similar reads from potentially large read set</li>
<li><a href="https://gatb.inria.fr/software/dsk/" title="DSK">DSK</a>:&nbsp;Count K-mer in sequences</li>
</ul><h2>Pangenome graph manipulation</h2><ul>
<li><a href="https://github.com/Tharos-ux/pancat">Pancat</a>: Pangenome Comparison and Analysis Toolkit</li>
<li><a href="https://pypi.org/project/gfagraphs/">GFAGraphs</a>: a Python library to handle pangenome graph files in GFA format.</li>
</ul><h2>Comparative metagenomics with k-mers</h2><ul>
<li><a href="https://github.com/GATB/simka">Simka and SimkaMin</a>:&nbsp;Comparative metagenomics for large-scale datasets</li>
<li><a href="https://team.inria.fr/genscale/high-throughput-sequence-analysis/compreads-metagenomic-data-analysis/">Comparead &amp; Commet</a>:&nbsp;comparison of metagenomic datasets</li>
</ul><h2>Species and bacterial strains identification</h2><ul>
<li><a href="https://github.com/gsiekaniec/ORI">ORI</a>: software using long nanopore reads to identify bacteria present in a sample at the strain level</li>
<li><a href="https://github.com/kevsilva/StrainFLAIR">StrainFLAIR</a>:&nbsp;STRAIN-level proFiLing using vArIation gRaph</li>
</ul><h2>General-purpose sequencing data manipulation</h2><ul>
<li><a href="https://team.inria.fr/genscale/ngs-software/gassst/">GASSST</a>:&nbsp;long read mapper</li>
<li><a href="https://gatb.inria.fr/software/leon/" title="Leon">Leon</a>: short read compressor (now included in GATB-core)</li>
<li><a href="https://gatb.inria.fr/software/bloocoo/" title="Bloocoo">Bloocoo</a>:&nbsp;short read corrector</li>
<li><a href="https://github.com/GATB/bcalm">BCALM</a>:&nbsp;Construct compacted de Bruijn graphs (unitigs)</li>
</ul><h2>&nbsp;Protein Structure</h2><ul>
<li><a href="https://team.inria.fr/genscale/protein-structure/a-purva-contact-map-overlap-solver/">A_Purva</a>:&nbsp;Contact Map Overlap solver</li>
<li><a href="https://team.inria.fr/genscale/protein-structure/md-jeep-distance-geomtry-solver/">MD-Jeep</a>:&nbsp;Distance Geometry solver</li>
<li><a href="https://team.inria.fr/genscale/csa-comparative-structural-alignment/">CSA</a>:&nbsp;Comparative Structural Alignment</li>
</ul><h2>Workflow</h2><ul>
<li><a href="https://team.inria.fr/genscale/workflows/slicee/">SLICEE</a>:&nbsp;parallel execution of bioinformatics workflows</li>
</ul><h3>Comparative Genomics</h3><ul>
<li><a href="https://team.inria.fr/genscale/comparative-genomics/cassis/">CASSIS</a>:&nbsp;detection of rearrangement breakpoints</li>
<li><a href="https://team.inria.fr/genscale/high-throughput-sequence-analysis/plast-intensive-sequence-comparison/">PLAST</a>:&nbsp;intensive bank-to-bank sequence comparison</li>
<li><a href="https://github.com/stephanierobin/DrjBreakpointFinder">DRJBreakpointFinder</a>: detection and precise localization of excision sites in proviral segments</li>
</ul>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:44:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</link>
	<title><![CDATA[Qualimap2: Evaluating next generation sequencing alignment data]]></title>
	<description><![CDATA[<p><strong>Qualimap 2</strong><span>&nbsp;is a platform-independent application written in Java and R that provides both a Graphical User Inteface (GUI) and a command-line interface to facilitate the quality control of alignment sequencing data and its derivatives like feature counts.&nbsp;</span><br><br><span>Supported types of experiments include:</span></p>
<ul>
<li>Whole-genome sequencing</li>
<li>Whole-exome sequencing</li>
<li>RNA-seq (speical mode available)</li>
<li>ChIP-seq</li>
</ul><p>Address of the bookmark: <a href="http://qualimap.bioinfo.cipf.es/" rel="nofollow">http://qualimap.bioinfo.cipf.es/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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