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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30701?offset=630</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28546/ra-bioinformatics-at-national-bureau-of-fish-genetic-resources</guid>
  <pubDate>Mon, 25 Jul 2016 03:14:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at  National Bureau of Fish Genetic Resources]]></title>
  <description><![CDATA[
<p>F.No. 1(16)/2016-Admn. (DBT-BBSRC Project)<br />Research Associate /JRF Biotechnology Job vacancies in National Bureau of Fish Genetic Resources on contract basis</p>

<p>Research Associate /01 Post</p>

<p>Essential: Ph.D. in Bioinformatics or 03 years research experience after Post Graduation in Bioinformatics with at least one research paper in Science Citation Indexed (SCI) journals.</p>

<p>Desirable:  The candidate should have at least 1st Division during Graduation and Post Graduation.  Experience in assembly/ analysis/ annotation of genomic/transcriptomic data generated on next generation sequencing platforms and working knowledge on different genomic softwares.  Publications in Relevant Field.</p>

<p>Pay Scale : Rs. 36,000/- +20% HRA </p>

<p>Age: 40 years for male and 45 years for female candidates, as on the date of interview</p>

<p>Junior Research Fellow/ 01 </p>

<p>Essential: Master Degree in Biotechnology/Life Science with Specialization in Molecular Biology with NET qualification. </p>

<p>Desirable:  Research Experience in Molecular Biology. 1st Division during Graduation as well as Post Graduation. Publications in Relevant Field.</p>

<p>Pay Scale: Rs. 25,000/-+ 20% HRA for 1st and 2nd year and Rs. 28,000/-+ 20% HRA for 3rd year</p>

<p>Age: 35 years for male and 40 years for female candidates, as on the date of interview.<br />How to apply<br />A walk-in-interview will be held on 26.07.2016 at 10:00 hrs. at ICAR-National Bureau of Fish Genetic Resources, Lucknow.</p>

<p>More at http://www.nbfgr.res.in/Recruitments.aspx</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28566/emboss-apps</guid>
	<pubDate>Wed, 27 Jul 2016 06:00:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28566/emboss-apps</link>
	<title><![CDATA[EMBOSS Apps]]></title>
	<description><![CDATA[<p>The programs are listed in alphabetical order, Look at the individual applications or go to the&nbsp;<a href="http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/groups.html">GROUPS</a>&nbsp;page to search by category.</p>
<p><a href="http://emboss.sourceforge.net/apps/release/6.6/embassy/index.html">EMBASSY applications</a>&nbsp;are described in separate documentation for each package.</p>
<h3><a name="current" id="current"></a>Applications&nbsp;in the&nbsp;<a href="ftp://emboss.open-bio.org/pub/EMBOSS/">current release</a></h3><p>Address of the bookmark: <a href="http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/" rel="nofollow">http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28602/srf-and-jrf-bioinformatics-at-tezpur-university-napaam</guid>
  <pubDate>Wed, 03 Aug 2016 03:47:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF and JRF Bioinformatics at Tezpur University, Napaam]]></title>
  <description><![CDATA[
<p>Applications are invited for the following temporary positions unde MHRD sponsored Centre of Excellence<br />in the Department of Computer Science and Engineering (CSE), Tezpur University<br /> <br />Qualification<br />and Experience : Senior Research Fellow (SRF) and JRF : First Class in M.E/M.Tech in CSE/IT/ECE with research<br />experience in relevant fields of research (Candidates having valid GATE/NET Score would be preferred).</p>

<p> <br />Fellowship: Rs. 18,000/- per month (fixed)<br /> <br />Duration : 2 (Two) years and may be extended<br />depending on status of the project<br /> <br />Age Limit: Candidates should not be more than 32 years of<br />age in case of SRF and 28 years of age in case of JRF and TA. Upper age limit may be relaxed up to 5<br />years in the case of candidate belonging to SC/ ST/ OBC/ Women/ Differently abled.<br /> <br />How to Apply:<br />Interested candidates may send their application on plain paper by post along with his/her educational<br />qualifications, research experience certificates (for SRF), 02 copies of recent passport/stamp size photographs<br />and contact phone number to Professor D.K Bhattacharyya, Principal Investigator, Department of Computer<br />Science &amp; Engineering, Tezpur University, Napaam – 784 028, or mail it to dkb@tezu.ernet.in<br />(or to smh@tezu.ernet.in) within 15 days of publication of this advertisement.<br /> <br />No TA/DA shall<br />be paid for attending the interview.<br /> <br />For more details: http://www.tezu.ernet.in/ProjectWalkin/Advt-DoRD-CSE-DKB-20-225-6779-A.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34862/pasa-gene-structure-annotation-and-analysis</guid>
	<pubDate>Tue, 26 Dec 2017 21:14:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34862/pasa-gene-structure-annotation-and-analysis</link>
	<title><![CDATA[PASA: Gene Structure Annotation and Analysis]]></title>
	<description><![CDATA[<p><span>PASA, acronym for Program to Assemble Spliced Alignments, is a eukaryotic genome annotation tool that exploits spliced alignments of expressed transcript sequences to automatically model gene structures, and to maintain gene structure annotation consistent with the most recently available experimental sequence data. PASA also identifies and classifies all splicing variations supported by the transcript alignments.</span></p><p>Address of the bookmark: <a href="http://pasapipeline.github.io/" rel="nofollow">http://pasapipeline.github.io/</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29017/walk-in-interview-jipmer</guid>
  <pubDate>Mon, 05 Sep 2016 04:01:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[WALK-IN INTERVIEW @ JIPMER]]></title>
  <description><![CDATA[
<p>Department of Preventive and Social Medicine<br />, JIPMER, Puducherry –605006</p>

<p>WALK-IN INTERVIEW</p>

<p>JIP/PSM/INDO-US TB/ 2016/</p>

<p>Walk-in-interview for the following vacant posts funded by Department of Biotechnology, Govt.of India for the project entitled “Biomarkers for Risk of Tuberculosis and for Tuberculosis Treatment Failure and Relapse” in the Department of Preventive &amp; Social Medicine, JIPMER, Puducherry.</p>

<p>3. Technical Assistant</p>

<p>MCA/ MSc in Biostatistics/ MSc in Computational Biology from any recognized University @ Rs.23,220 1</p>

<p>Interested candidates may attend the walk-in interview with written screening test on 07, September 2016 at 9.30 A.M in the Dept. of Preventive and Social Medicine, IV Floor, Administrative Block, JIPMER.</p>

<p>The applicants are requested to bring the filled in application form and bio-data with original certificates for verification.</p>

<p>More Info: http://jipmer.edu.in/wp-content/uploads/2016/09/RECRUITEMENTsite-protocol-7.9.2016.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37230/navigator-network-analysis-visualization-and-graphing-toronto</guid>
	<pubDate>Tue, 03 Jul 2018 05:05:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37230/navigator-network-analysis-visualization-and-graphing-toronto</link>
	<title><![CDATA[NAViGaTOR: Network Analysis, Visualization and Graphing Toronto]]></title>
	<description><![CDATA[NAViGaTOR –  Network Analysis, Visualization, &amp; Graphing TORonto is a software system for scaleable visualizing and analyzing networks.

The current version, NAViGaTOR 3, increases modularity, improves scaleability, extends input/output options, brings new network views and analysis algorithms.

http://142.150.188.236/navigatorwp/<p>Address of the bookmark: <a href="http://142.150.188.236/navigatorwp/" rel="nofollow">http://142.150.188.236/navigatorwp/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37982/raven-a-software-suite-for-matlab-that-allows-for-semi-automated-reconstruction-of-genome-scale-models</guid>
	<pubDate>Wed, 24 Oct 2018 22:38:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37982/raven-a-software-suite-for-matlab-that-allows-for-semi-automated-reconstruction-of-genome-scale-models</link>
	<title><![CDATA[RAVEN: a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models]]></title>
	<description><![CDATA[<p><span>The RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox 2 is a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models (GEMs). It makes use of published models and/or KEGG, MetaCyc databases, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology.</span></p><p>Address of the bookmark: <a href="https://github.com/SysBioChalmers/RAVEN" rel="nofollow">https://github.com/SysBioChalmers/RAVEN</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41820/shinygo-v061-gene-ontology-enrichment-analysis-more</guid>
	<pubDate>Wed, 03 Jun 2020 08:00:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41820/shinygo-v061-gene-ontology-enrichment-analysis-more</link>
	<title><![CDATA[ShinyGO v0.61: Gene Ontology Enrichment Analysis + more]]></title>
	<description><![CDATA[<p>2/3/2020: Now published by&nbsp;<a href="https://doi.org/10.1093/bioinformatics/btz931" target="_blank">Bioinformatics.</a></p>
<p>11/3/2019: V 0.61, Improve graphical visualization (thanks to reviewers). Interactive networks and much more.</p>
<p>5/20/2019: V.0.60, Annotation database updated to Ensembl 96. New bacterial and fungal genomes based on STRING-db! Just paste your gene list to get enriched GO terms and othe pathways for over 315 plant and animal species, based on annotation from Ensembl (Release 96), Ensembl plants (R. 43) and Ensembl Metazoa (R. 43). An additional 2031 genomes (including bacteria and fungi) are annotated based on STRING-db (v.10). In addition, it also produces KEGG pathway diagrams with your genes highlighted, hierarchical clustering trees and networks summarizing overlapping terms/pathways, protein-protein interaction networks, gene characterristics plots, and enriched promoter motifs.&nbsp;</p><p>Address of the bookmark: <a href="http://bioinformatics.sdstate.edu/go/" rel="nofollow">http://bioinformatics.sdstate.edu/go/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44188/understanding-go-analysis</guid>
	<pubDate>Wed, 08 Feb 2023 04:22:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44188/understanding-go-analysis</link>
	<title><![CDATA[Understanding GO analysis]]></title>
	<description><![CDATA[<p>The confusion about gene ontology and gene ontology analysis can start right from the term itself. There are actually two different entities that are commonly referred to as gene ontology or &ldquo;GO&rdquo;:</p>
<ol>
<li>the&nbsp;<span>ontology itself</span>, which is a set of terms with their precise definitions and defined relationships between them, and</li>
<li>the&nbsp;<span>associations between gene products and GO terms</span>, which are used to capture the existing knowledge about what each gene is known to do.</li>
</ol>
<p>But the term gene ontology, or GO, is commonly used to refer to both, which is sometimes a source of potential confusion. In order to avoid this, here we will use the term &ldquo;GO ontology&rdquo; to describe the set of terms and their hierarchical structure and &ldquo;GO annotations&rdquo; to describe the set of associations between genes and GO terms.</p>
<p>There are 3 types of terms, or domains if you wish, in the gene ontology:</p>
<ul>
<li>Biological Processes (BP)</li>
<li>Molecular Functions (MF)</li>
<li>Cellular Components (CC)</li>
</ul><p>Address of the bookmark: <a href="https://advaitabio.com/faq-items/understanding-gene-ontology/" rel="nofollow">https://advaitabio.com/faq-items/understanding-gene-ontology/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44620/diy-transcriptomics</guid>
	<pubDate>Wed, 31 Jul 2024 01:19:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44620/diy-transcriptomics</link>
	<title><![CDATA[DIY Transcriptomics]]></title>
	<description><![CDATA[<p><span>A semester-long course covering best practices for the analysis of high-throughput sequencing data from gene expression (RNA-seq) studies, with a primary focus on empowering students to be independent in the use of lightweight and open-source software using the R programming language and the Bioconductor suite of packages. This course follows a hybrid format in which online lectures are paired with in-person labs where students participate in hands-on, live coding exercises using real &lsquo;omic datasets. The course is focused on datasets and topics central to infectious disease research, immunology, and One-Health, but the concepts and approaches covered are applicable to any genomic study.</span></p>
<p>https://diytranscriptomics.com</p><p>Address of the bookmark: <a href="https://diytranscriptomics.com" rel="nofollow">https://diytranscriptomics.com</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

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