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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28269?offset=850</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26587/last</guid>
	<pubDate>Wed, 09 Mar 2016 14:27:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26587/last</link>
	<title><![CDATA[LAST]]></title>
	<description><![CDATA[<p style="text-align: center;"><img src="http://last.cbrc.jp/lastwebfig.png" alt="sketch of  similar regions in sequences" style="border: 0px;"></p>
<p>LAST can:</p>
<ul>
<li>Handle <strong>big</strong> sequence data, e.g:
<ul>
<li>Compare two vertebrate genomes</li>
<li>Align billions of DNA reads to a genome</li>
</ul>
</li>
<li>Indicate the <a href="http://lastweb.cbrc.jp/about.html">reliability</a> of each aligned column.</li>
<li>Use sequence quality data <a href="http://nar.oxfordjournals.org/content/38/7/e100.abstract">properly</a>.</li>
<li>Compare DNA to proteins, with frameshifts.</li>
<li>Compare PSSMs to sequences</li>
<li>Calculate the likelihood of chance similarities between random sequences.</li>
<li>Do split and spliced alignment.</li>
<li><a href="http://last.cbrc.jp/doc/last-train.html">Train</a> alignment parameters for unusual kinds of sequence (e.g. nanopore).</li>
</ul><p>Address of the bookmark: <a href="http://last.cbrc.jp/" rel="nofollow">http://last.cbrc.jp/</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<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/opportunity/view/25308/traineeship-at-biomedical-informatics-centre-pgimer-chandigarh</guid>
  <pubDate>Sun, 29 Nov 2015 03:04:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[Traineeship at Biomedical Informatics Centre  PGIMER  Chandigarh]]></title>
  <description><![CDATA[
<p>Biomedical Informatics Centre</p>

<p>PGIMER</p>

<p>Chandigarh</p>

<p>invites application for a project dissertation program for students who have completed their first year of M.Sc. in Bioinformatics.</p>

<p>This is an exciting opportunity for Master's students to train in modern methods in Bioinformatics. The duration of the training will be four to six months, starting from January 2016.</p>

<p>Education: Pursuing M.Sc. Bioinformatics</p>

<p>Essential: Post graduate applicants should have completed their first year and should be in the third semester or first half of the second year.</p>

<p>Only students who are willing to spend a minimum period of 4 months to a maximum of six months, without any break, would be eligible for the program.</p>

<p>How to Apply: Candidates interested in the above project dissertation program should apply online. Send your CV, Scanned copy of letter of recommendation from Head of Institution along with Registration form in the given format should be sent to: info@bicpgi.org</p>

<p>Please mention clearly “Project dissertation &amp; your Name” in the Subject.</p>

<p>The last date for application is December 23, 2015</p>

<p>Note: Selected candidates may please note that the program is free of cost and would not provide any financial aid for transport and stay. Name of the selected candidates would be posted on the centre website by December 31, 2015.</p>

<p>Incomplete applications will be rejected.</p>

<p>For more information visit our website: http://bic-pgi.org/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology</guid>
	<pubDate>Tue, 19 Dec 2017 18:49:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology</link>
	<title><![CDATA[1mb long DNA with Nanopore technology]]></title>
	<description><![CDATA[<p>The first continuous DNA read of more than a million bases (&gt;1Mb) has been achieved, using Oxford Nanopore sequencing technology. Congratulations to Martin Smith and collaborators! Read more: http://bit.ly/2j5TNCO</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25302/ra-bioinformatics-at-jamia-hamdard</guid>
  <pubDate>Sat, 28 Nov 2015 03:37:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at Jamia Hamdard]]></title>
  <description><![CDATA[
<p>Research Associate, Bioinformatics Facility<br />Jamia Hamdard - New Delhi, Delhi<br />Research Associate, Bioinformatics Facility, Jamia Hamdard.<br />Emoluments: Rs. 22,000 + HRA 30%<br />Qualification: PhD or equivalent or having 3 years of research, teaching and design and development experience after M. Pharm./M.VSc./M.E./M.Tech. PhD in life sciences and related areas with experience in Bioinformatics may apply. Company Info.<br />Jamia Hamdard</p>

<p>Jamia Hamdard New Delhi - 110062 Additional Information States &amp; U.T State &amp; Union Territories Delhi How To Apply Apply Details<br />Last date of application: December 5, 2015 Web/Notification URL http://www.jamiahamdard.ac.in/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38535/nanopack-visualizing-and-processing-long-read-sequencing-data</guid>
	<pubDate>Tue, 25 Dec 2018 21:20:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38535/nanopack-visualizing-and-processing-long-read-sequencing-data</link>
	<title><![CDATA[NanoPack: visualizing and processing long-read sequencing data]]></title>
	<description><![CDATA[The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.<p>Address of the bookmark: <a href="https://github.com/wdecoster/nanopack" rel="nofollow">https://github.com/wdecoster/nanopack</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</guid>
	<pubDate>Tue, 28 Jan 2020 03:21:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</link>
	<title><![CDATA[Kevler: Reference-free variant discovery in large eukaryotic genomes]]></title>
	<description><![CDATA[<p><span>Welcome to&nbsp;</span><span>kevlar</span><span>, software for predicting&nbsp;</span><em>de novo</em><span>&nbsp;genetic variants without mapping reads to a reference genome! kevlar's&nbsp;</span><em>k</em><span>-mer abundance based method calls single nucleotide variants (SNVs), multinucleotide variants (MNVs), insertion/deletion variants (indels), and structural variants (SVs) simultaneously with a single simple model.&nbsp;</span></p>
<p><span>More at&nbsp;<a href="https://kevlar.readthedocs.io/en/latest/">https://kevlar.readthedocs.io/en/latest/</a></span></p>
<p><span><a href="https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf">https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf</a></span></p><p>Address of the bookmark: <a href="https://github.com/kevlar-dev/kevlar" rel="nofollow">https://github.com/kevlar-dev/kevlar</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25504/uas-dharwad-assistant-professor</guid>
  <pubDate>Fri, 04 Dec 2015 21:06:23 -0600</pubDate>
  <link></link>
  <title><![CDATA[UAS Dharwad Assistant Professor]]></title>
  <description><![CDATA[
<p>UNIVERSITY OF AGRICULTURAL SCIENCES, DHARWAD</p>

<p>Applications are invited in the prescribed form for filling up the following posts of Teachers and Service Personnel from the candidates who are qualified as on the last date fixed for receipt of applications in the University of Agricultural Sciences, Dharwad.</p>

<p>I. ASSISTANT PROFESSOR CADRE (Scale of pay Rs.15600-39100 + AGP Rs. 6000) (UGC / ICAR pay-scales)</p>

<p>I. Re-notified posts:</p>

<p>9. Assistant Professor of Bioinformatics 1 GM-1</p>

<p>More Info : https://sites.google.com/a/uasd.in/recruitment/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25770/fellowship-doctoral-research-in-biomedical-genomics-including-statistical-genomics</guid>
  <pubDate>Sun, 20 Dec 2015 06:03:43 -0600</pubDate>
  <link></link>
  <title><![CDATA[Fellowship (Doctoral Research In Biomedical Genomics, Including Statistical Genomics)]]></title>
  <description><![CDATA[
<p>Fellowship (Doctoral Research In Biomedical Genomics, Including Statistical Genomics)<br />Eligibility : MSc(Bio-Chemistry, Bio-Informatics, Bio-Tech, Mathematics / Applied Mathematics, Stati, Zoology)<br />Location : Kolkata<br />Last Date : 31 Dec 2015<br />Hiring Process : Written-test</p>

<p>NO: 340/ESTB/ADMN/NIBMG/2015-16 <br />Doctoral Research In Biomedical Genomics, Including Statistical Genomics conduct National Institute of Biomedical Genomics (NIBMG)<br />Information For Students Interested To Pursue Doctoral Research In Biomedical Genomics, Including Statistical Genomics, At The National Institute Of Biomedical Genomics (Nibmg), Kalyan<br />Eligibility conditions for specific areas of research are :<br />Statistical Genomics : An applicant who wishes to pursue research in Statistical Genomics should hold a Master's degree (First class or equivalent) in a relevant discipline (Statistics, Mathematics, Bioinformatics, or a related discipline)<br />Biomedical Genomics : An applicant who wishes to pursue research in any area of biomedical genomics, other than statistical genomics, should hold a Master's degree (First class or equivalent) in a relevant discipline (Biochemistry, Biotechnology, Molecular Biology, Genetics, Zoology, Physiology, or a related discipline)<br />Fellowship : An applicant should have passed the NET conducted by CSIR/UGC/ICMR/DBT within the past ONE year AND should have been awarded a valid Junior Research Fellowship from CSIR, UGC, ICMR, DBT (Category-I only), DST (INSPIRE), NBHM. Preference will be given to candidates with demonstrable research training in the form of summer training or short-term courses in established research laboratories in preparation for a research career in biomedical sciences<br />How to apply<br />Online application will be accepted until 5 PM of December 31, 2015. A formal interview of the short-listed candidates will be held on January 12, 2016</p>

<p>More at http://www.nibmg.ac.in/?q=Career%20Opportunities</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26568/research-scientist-at-iit-madras</guid>
  <pubDate>Mon, 07 Mar 2016 04:06:13 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Scientist at IIT Madras]]></title>
  <description><![CDATA[
<p>Research Scientist/Project Associate/Project Assistant Jobs opportunity in Indian Institute of Technology Madras (IIT Madras)</p>

<p>Research Scientist</p>

<p>Qualification : Ph.D in any branch of life science or bioinformatics or computational biology Experience : Previous experience in Molecular Biology, Cell Biology, Biochemistry and Genome/big data analysis is desirable but not mandatory</p>

<p>No. of Vacancy : 02</p>

<p>Project Associate</p>

<p>Qualification : MSc in any branch of life science Experience Previous experience in Molecular Biology, Cell Biology and Biochemistry is desirable but not mandatory</p>

<p>No. of Vacancy : 02</p>

<p>Project Assistant</p>

<p>Qualification : BSc in any branch of life science or chemical science Experience Previous experience any branch in Life science, Molecular Biology, Cell Biology and Biochemistry is desirable but not mandatory</p>

<p>No. of Vacancy : 03<br />How to apply</p>

<p>Interested candidates can forward their profiles to email id: nctb@iitm.ac.in latest by 18th March, 2016</p>

<p>More at https://www.iitm.ac.in/content/national-cancer-tissue-bio-bank-department-biotechnology-iitm-chennai-vacancy-various-post<br />https://www.iitm.ac.in/sites/default/files/notices/vacancy.pdf</p>
]]></description>
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