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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26380?offset=550</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/2518/genome-browsers</guid>
	<pubDate>Fri, 16 Aug 2013 19:04:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/2518/genome-browsers</link>
	<title><![CDATA[Genome Browsers]]></title>
	<description><![CDATA[<p>Genome Browser is the platform/database used for searching and retreiving sequences and annotation of genomes belong to various eukaryotes, prokaryotes, etc.</p><p>Following are the weblink for different available browsers:</p><p><a href="http://www.ensembl.org/index.html">http://www.ensembl.org/index.html</a></p><p><a href="http://ensemblgenomes.org/">http://ensemblgenomes.org/</a></p><p><a href="http://genome.ucsc.edu/">http://genome.ucsc.edu/</a></p><p><a href="http://www.ncbi.nlm.nih.gov/genome">http://www.ncbi.nlm.nih.gov/genome</a></p><p><a href="http://www.ebi.ac.uk/genomes/">http://www.ebi.ac.uk/genomes/</a></p><p><a href="http://flybase.org/">http://flybase.org/</a></p><p><a href="http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi">http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi</a></p><p><a href="http://www.sanger.ac.uk/resources/databases/">http://www.sanger.ac.uk/resources/databases/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/40248/industrial-training-in-computer-aided-drug-designing-cadd</guid>
	<pubDate>Wed, 13 Nov 2019 05:00:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/40248/industrial-training-in-computer-aided-drug-designing-cadd</link>
	<title><![CDATA[Industrial Training in Computer Aided Drug Designing (CADD)]]></title>
	<description><![CDATA[<p>Learn More about&nbsp; Computer Aided Drug Designing (CADD)!!!</p><p>#rasalsi #rasa In our Industrial program you will get Knowledge on RNA Seq, CHIP Seq,</p><h2 style="text-align: center;"><strong>Batch Starts From 18<sup>th</sup> November 2019</strong></h2><p>#hurryup #registernow #enquirenow The primary goal of the industrial training program is to provide students with necessary skills making with employable. RASA LSI trains students with the enhanced skills required for them to excel in jobs in biotechnology, pharmaceuticals, BioIT and related industry sectors. At Rasa you will&nbsp; learn from industry leaders&nbsp;how to apply these skills in life science &amp; have a command over software developing process &nbsp;by using various methodologies. For Registration visit us on: https://www.rasalsi.com/index.php/front-page/industrial-training/</p>]]></description>
	<dc:creator>RASA Life Sciences</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41041/post-doc-computational-biology-bioinformatics-network-biology-data-science-ngs-mfd</guid>
  <pubDate>Sat, 15 Feb 2020 06:13:35 -0600</pubDate>
  <link></link>
  <title><![CDATA[Post Doc Computational Biology, Bioinformatics - Network Biology &amp; Data Science, NGS (m/f/d)]]></title>
  <description><![CDATA[
<p>https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/forschung-entwicklung/post-doc-computational-biology-bioinformatics-network-biology-data-science-ngs-129867.html?suid=e522e9793b41817e52ac58d6963b94e2519920df</p>

<p>Requirements<br />Doctoral degree in Bioinformatics, Computational Biology, (Bio)physics/-mathematics, Biochemistry/Biology or similar with strong quantitative and numeric focus<br />Ability to numerically process complex and large data sets<br />Good programming skills (R/Bioconductor and/or Python preferred, Linux is a plus)<br />Experience in analyzing next-generation sequencing data sets using network biology<br />Scientific publication record in applied bioinformatics<br />Familiarity with single cell NGS analyses and other –omics techniques is a plus, but not essential</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41924/senior-scientist-bioinformatics-it-at-regional-centre-for-biotechnology</guid>
  <pubDate>Tue, 30 Jun 2020 22:04:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Scientist (Bioinformatics/ IT) at Regional Centre for Biotechnology]]></title>
  <description><![CDATA[
<p>Regional Centre for Biotechnology</p>

<p>An Institution of National Importance established by Dept. of<br />Biotechnology, Govt. of India Under the auspices of UNESCO</p>

<p>Advertisement No. RCB/IBDC/01/2020/Recruitment/HR</p>

<p>Recruitment For Contractual Positions Under The Project<br />Indian Biological Data Centre (IBDC) Phase-1</p>

<p>Regional Centre for Biotechnology (RCB) invites online applications from suitably qualified, dynamic, result-oriented and dedicated candidates for the following positions under the project Indian Biological Data Centre (BIDC) Phase-1 on contract basis:</p>

<p>Industry: Biotechnology</p>

<p>Location: Faridabad (Haryana, India)</p>

<p>Project Head - 1</p>

<p>Senior Scientist (Bioinformatics/ IT) - 1</p>

<p>For other details, visit: www.rcb.res.in. Last date for receipt of online application is 18th July 2020.</p>

<p>Registrar</p>

<p>Regional Centre for Biotechnology<br />Faridabad-Gurgaon Expressway,<br />Faridabad - 121001</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33221/genome-annotation-transfer-utility-gatu</guid>
	<pubDate>Mon, 29 May 2017 05:54:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33221/genome-annotation-transfer-utility-gatu</link>
	<title><![CDATA[Genome Annotation Transfer Utility (GATU)]]></title>
	<description><![CDATA[<p>Genome Annotation Transfer Utility (GATU) was designed to facilitate quick, efficient annotation of similar genomes using genomes that have already been annotated. For example, whenever a new strain of SARS coronavirus is sequenced, it is possible, using GATU, to automatically annotate the new strain using a previously-annotated strain of SARS CoV. This saves researchers from tedious manual annotation of these sequences.</p>
<p>The program utilizes tBLASTn and BLASTn algorithms to map genes from the reference genome (the annotated strain) to the new sequence (the unannotated strain). The goal is to annotate the majority of the new genome&rsquo;s genes in a single step. ORFs present in the target genome and absent from the reference genome are also identified; these ORFs can be further analyzed using BLAST, VGO and BBB. Afterwards, they can either be accepted for/rejected from annotation. GATU can handle multiple-exon genes as well as mature peptides. Although it was designed for use with viral genomes, GATU can also be used to help annotate larger genomes (ie. bacterial genomes).</p>
<p>The output is saved in GenBank, XML, or EMBL file format.</p><p>Address of the bookmark: <a href="https://virology.uvic.ca/help/tool-help/help-books/genome-annotation-transfer-utility-gatu-documentation/" rel="nofollow">https://virology.uvic.ca/help/tool-help/help-books/genome-annotation-transfer-utility-gatu-documentation/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42172/sr-scientist-bioinformatics-vacancies-at-indian-institute-of-toxicology-research-india</guid>
  <pubDate>Tue, 01 Sep 2020 07:21:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[Sr. Scientist Bioinformatics Vacancies at Indian Institute of Toxicology Research, India]]></title>
  <description><![CDATA[
<p>Start date of online Registration: Wednesday August 19, 2020 11:00 Hrs IST<br />Last date for Registration: Monday September 21, 2020 17:30 Hrs IST<br />Last date for submission of online application: Monday September 21, 2020 17:30 Hrs IST<br />Last date of Receipt of physical copy of application at CSIR-IITR: Tuesday October 05, 2020 17:30 Hrs IST</p>

<p>Pay Matrix Level-12<br />No. of Post-01<br />(UR)<br />Post – Sr. Scientist<br />Area Bioinformatics<br />Age limit : 37 years<br />PhD in Computational Biology/Bioinformatics with 2 years experience in desired area<br />Or<br />ME/M.Tech in Bioinformatics or Genome Informatics or Genetic Engineering with 3 years experience in desired area<br />Experience of understanding fundamental science behind Artificial Intelligence, machine learning, novel Artificial Intelligence algorithms and architectures, software engineering principles for Artificial Intelligence, natural language processing with proficiency in programming as evident by publications in SCI journals with high impact factor. To be part a group of scientists working in the area of genomics, running the central<br />bioinformatics facility, developing independent projects and providing bioinformatics support to the user scientists of the Institute.</p>

<p>More at </p>

<p>http://14.139.62.50/CSIR-IITR%20Scientist%20Recruitment%20Adv%202020.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</guid>
	<pubDate>Thu, 20 Dec 2018 17:39:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</link>
	<title><![CDATA[Genome Annotation using MAKER tutorial !]]></title>
	<description><![CDATA[<p><a href="http://www.yandell-lab.org/software/maker.html">MAKER</a><span>&nbsp;is a great tool for annotating a reference genome using empirical and&nbsp;</span><em>ab initio</em><span>gene predictions.&nbsp;</span><a href="http://gmod.org/wiki/Main_Page">GMOD</a><span>, the umbrella organization that includes MAKER, has some nice tutorials online for running MAKER. However, these were quite simplified examples and it took a bit of effort to wrap my head completely around everything. Here I will describe a&nbsp;</span><em>de novo</em><span>&nbsp;genome annotation for&nbsp;</span><em>Boa constrictor</em><span>&nbsp;in detail, so that there is a record and that it is easy to use this as a guide to annotate any genome.</span></p><p>Address of the bookmark: <a href="https://www.biostars.org/p/261203/" rel="nofollow">https://www.biostars.org/p/261203/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42264/bioinformatics-jobs-at-acrannolife</guid>
  <pubDate>Sun, 25 Oct 2020 22:51:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics jobs at Acrannolife]]></title>
  <description><![CDATA[
<p>Acrannolife are looking for skilled Bioinformatics Scientists with a minimum of 2yrs Experience in NGS data analysis including Nanopore Sequencing.</p>

<p>This is an opportunity to work on projects that would fundamentally alter the way certain chronic conditions are treated and monitored.</p>

<p>About acrannolife:</p>

<p>We are a team of Post Docs, PhDs, Engineers, Clinicians, and MBAs working towards a future where biology intersects with software(Computational Biology).</p>

<p>We are incubated in Atal Incubation Centre - CCMB and have been backed by some of the leading thought leaders ranging from business to clinical practices.</p>

<p>Interested candidates can fill this form. https://lnkd.in/gtq47hy</p>

<p>and send their CV to hr@acrannolife.com</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42374/postdoc-in-comparative-genomics</guid>
  <pubDate>Tue, 08 Dec 2020 09:26:40 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoc in comparative genomics]]></title>
  <description><![CDATA[
<p>We are looking for a highly motivated researcher for an 18 month postdoctoral position collaborating in an exciting project on comparative genomics of marine fish and shellfish species. In the project, we use genome resequencing data from a range of species to reconstruct the demographic history and characterize genomic signals associated with population divergence and local adaptation in high gene flow scenarios. The work will improve our understanding of interacting evolutionary processes and provide valuable data for securing sustainable management and conservation of exploited resources. Applicants are encouraged to develop their own research ideas within this framework.</p>

<p>The fellowship is part of a larger Nordic collaborative project, MarGen_II, financed by the EU Interreg Öresund-Kattegat-Skagerrak Programme, the Danish Rod and Net License Funds and the National Institute of Aquatic Resources (DTU Aqua). The project will primarily be carried out in the population genetics group, Section for Marine Living Resources, situated in Silkeborg, Denmark. DTU Aqua is an institute at the Technical University of Denmark. In addition, the position offers many opportunities for collaborating with Nordic and other European colleagues in the field.</p>

<p>Application:<br />Apply online at<br />https://www.dtu.dk/english/About/JOB-and-CAREER/vacant-positions/job?id=d198fd80-4856-4a56-943d-485106026504.<br />The deadline is 4 January 2021. For further information, please contact<br />Senior Researcher Jakob Hemmer-Hansen, jhh@aqua.dtu.dk.</p>

<p>You can read more about DTU Aqua at www.aqua.dtu.dk<br />and the population genetics group at<br />https://www.aqua.dtu.dk/english/research/population_genetics.</p>

<p>All interested candidates irrespective of age, gender, race, disability,<br />religion or ethnic background are encouraged to apply.</p>

<p>Jakob Hemmer Hansen</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34328/dfast-a-flexible-prokaryotic-genome-annotation-pipeline-for-faster-genome-publication</guid>
	<pubDate>Tue, 14 Nov 2017 10:26:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34328/dfast-a-flexible-prokaryotic-genome-annotation-pipeline-for-faster-genome-publication</link>
	<title><![CDATA[DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication]]></title>
	<description><![CDATA[<p>We developed a prokaryotic genome annotation pipeline, DFAST, that also supports genome submission to public sequence databases. DFAST was originally started as an on-line annotation server, and to date, over 7,000 jobs have been processed since its first launch in 2016. Here, we present a newly implemented background annotation engine for DFAST, which is also available as a standalone command-line program. The new engine can annotate a typical-sized bacterial genome within 10 minutes, with rich information such as pseudogenes, translation exceptions, and orthologous gene assignment between given reference genomes. In addition, the modular framework of DFAST allows users to customize the annotation workflow easily and will also facilitate extensions for new functions and incorporation of new tools in the future.</p>
<div>Availability and Implementation</div>
<p>The software is implemented in Python 3 and runs in both Python 2.7 and 3.4&ndash; on Macintosh and Linux systems. It is freely available at&nbsp;<a href="https://github.com/nigyta/dfast_core/" target="">https://github.com/nigyta/dfast_core/</a>&nbsp;under the GPLv3 license with external binaries bundled in the software distribution. An on-line version is also available at&nbsp;<a href="https://dfast.nig.ac.jp/" target="">https://dfast.nig.ac.jp/</a>.</p><p>Address of the bookmark: <a href="https://dfast.nig.ac.jp/" rel="nofollow">https://dfast.nig.ac.jp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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