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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32379?offset=600</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42042/cluego-a-cytoscape-plug-in-that-visualizes-the-non-redundant-biological-terms-for-large-clusters-of-genes</guid>
	<pubDate>Thu, 13 Aug 2020 10:24:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42042/cluego-a-cytoscape-plug-in-that-visualizes-the-non-redundant-biological-terms-for-large-clusters-of-genes</link>
	<title><![CDATA[ClueGO: a Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes]]></title>
	<description><![CDATA[<p>ClueGO is a Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network and it can be used in combination with GOlorize. The identifiers can be uploaded from a text file or interactively from a network of Cytoscape. The type of identifiers supported can be easely extended by the user. ClueGO performs single cluster analysis and comparison of clusters. From the ontology sources used, the terms are selected by different filter criteria. The related terms which share similar associated genes can be fused to reduce redundancy. The ClueGO network is created with kappa statistics and reflects the relationships between the terms based on the similarity of their associated genes. On the network, the node colour can be switched between functional groups and clusters distribution. ClueGO charts are underlying the specificity and the common aspects of the biological role. The significance of the terms and groups is automatically calculated. ClueGO is easy updatable with the newest files from Gene Ontology and KEGG.</p><p>Address of the bookmark: <a href="http://www.ici.upmc.fr/cluego/" rel="nofollow">http://www.ici.upmc.fr/cluego/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5958/srfjrf-national-institute-of-immunology</guid>
  <pubDate>Wed, 30 Oct 2013 06:45:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF/JRF @ National Institute of Immunology]]></title>
  <description><![CDATA[
<p>ADVERTISEMENT OF WALK-IN-INTERVIEW</p>

<p>NAME OF THE POST : SRF/JRF (Four Posts only)</p>

<p>DURATION : Indicated with the respective project mentioned below:</p>

<p>NAME OF THE PROJECT : As Mentioned below:</p>

<p>1. Serological diversity and molecular characterization of Dichelobector nodusus and development of vaccine against virulent footroot funded by NAIP. (Tenable upto 31.03.2014)</p>

<p>2. Development of oral vaccine against Clostridium perfringenes employing translational fusion of immunodominant epitopes of beta toxin with heat labile entertoxin B funded by DBT. (Tenable upto 25.02.2014)</p>

<p>3. Indo-Norwegian project, “Evaluation of major porins, ompC and ompR of Areomonas hydrophila as potential vaccine candidates and identification and characterization of immune genes of Indian major carp, Labeo rohita” (Tenable upto 31.03.2014)</p>

<p>EDUCATIONAL QUALIFICATIONS: For JRF- M.Sc/M.Tech in any subject of Biological  Sciences/Life Sciences</p>

<p>For SRF- M.Sc/M.Tech in any subject of Biological Sciences/Life Sciences with 2 years of Research Experience.</p>

<p>JOB DESCRIPTION : The Candidate should have experience in gene Expression, protein purification, molecular biology techniques and bioinformatics<br />EMOLUMENTS : SRF: Rs. 18,000/- per month consolidated plus 30% HRA if /NET/GATE qualified otherwise Rs. 14,000/- per month consolidated + 30% HRA.</p>

<p>JRF: Rs. 16,000/- per month consolidated + 30% HRA if NET/GATE qualified otherwise Rs. 12,000/- per month consolidated + 30% HRA</p>

<p>SCIENTIST NAME : Dr. Lalit C. Garg, SS-VII (Gene Regulation Lab)</p>

<p>SCIENTIST’S EMAIL : lalit@nii.ac.in</p>

<p>WALK IN INTERVIEW ON : October 31st, 2013</p>

<p>REGISTRATION OF CANDIDATES: 10.30 AM to 11.00 AM </p>

<p>Advertisement: http://www1.nii.res.in/sites/default/files/project-Dr.Lalit-31oct2013.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43013/deg-50-a-database-of-essential-genes-in-both-prokaryotes-and-eukaryotes</guid>
	<pubDate>Tue, 30 Mar 2021 11:47:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43013/deg-50-a-database-of-essential-genes-in-both-prokaryotes-and-eukaryotes</link>
	<title><![CDATA[DEG 5.0: a database of essential genes in both prokaryotes and eukaryotes]]></title>
	<description><![CDATA[<p><span>Essential genes are those indispensable for the survival of an organism, and their functions are therefore considered a foundation of life. Determination of a minimal gene set needed to sustain a life form, a fundamental question in biology, plays a key role in the emerging field, synthetic biology. </span></p>
<p><span></span><span>DEG is freely available at the website&nbsp;</span><a href="http://tubic.tju.edu.cn/deg" target="_blank">http://tubic.tju.edu.cn/deg</a><span>&nbsp;or&nbsp;</span><a href="http://www.essentialgene.org/" target="_blank">http://www.essentialgene.org</a><span>.</span></p><p>Address of the bookmark: <a href="http://www.essentialgene.org/" rel="nofollow">http://www.essentialgene.org/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6104/incob-2014</guid>
  <pubDate>Thu, 07 Nov 2013 17:53:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[InCoB 2014]]></title>
  <description><![CDATA[
<p>The 13th International Conference on Bioinformatics (InCoB 2014) will be held in Novotel Sydney Brighton Beach, Sydney, New South Wales, Australia. This year, the InCoB will be held earlier from 31st July to 2nd August 2014 to run back-to-back with the International Biophysics Congress 2014 at the Brisbane Convention and Exhibition Centre, Queensland (3-7 Aug).</p>

<p>More at http://incob2014.org/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44479/doubletrouble-identify-duplicated-genes-from-whole-genome-protein-sequences-and-classify</guid>
	<pubDate>Tue, 05 Mar 2024 00:23:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44479/doubletrouble-identify-duplicated-genes-from-whole-genome-protein-sequences-and-classify</link>
	<title><![CDATA[doubletrouble: identify duplicated genes from whole-genome protein sequences and classify]]></title>
	<description><![CDATA[<p><span>doubletrouble aims to identify duplicated genes from whole-genome protein sequences and classify them based on their modes of duplication. The duplication modes are i. segmental duplication (SD); ii. tandem duplication (TD); iii. proximal duplication (PD); iv. transposed duplication (TRD) and; v. dispersed duplication (DD). Transposon-derived duplicates (TRD) can be further subdivided into rTRD (retrotransposon-derived duplication) and dTRD (DNA transposon-derived duplication). If users want a simpler classification scheme, duplicates can also be classified into SD- and SSD-derived (small-scale duplication) gene pairs. Besides classifying gene pairs, users can also classify genes, so that each gene is assigned a unique mode of duplication. Users can also calculate substitution rates per substitution site (i.e., Ka and Ks) from duplicate pairs, find peaks in Ks distributions with Gaussian Mixture Models (GMMs), and classify gene pairs into age groups based on Ks peaks.</span></p><p>Address of the bookmark: <a href="https://bioconductor.org/packages/release/bioc/html/doubletrouble.html" rel="nofollow">https://bioconductor.org/packages/release/bioc/html/doubletrouble.html</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/6300/list-of-bioinformatics-vacancy-jobs-opportunity-websites</guid>
	<pubDate>Tue, 12 Nov 2013 20:04:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/6300/list-of-bioinformatics-vacancy-jobs-opportunity-websites</link>
	<title><![CDATA[List of Bioinformatics Vacancy, Jobs, Opportunity websites]]></title>
	<description><![CDATA[<p>Bioinformatics cover wide area of biology, and indulge in almost all sort of science related work. Bioinformatician give strong emphasis on open access to biological information as well as Free and Open Source software!!</p>
<p>There are several jobs opening in bioinformatics all around the world, but many of them do not get proper attention due to lack of advertisements, or social connectivity. This bookmark is created for an academic, non-academic, scientists and budding researchers to help and updates the bioinformatics/computational biology jobs links of all know websites around the world.</p>
<p><strong>I also love to stream the live <strong>bioinformatics or Computational biology jobs</strong> updates using Twitter https://twitter.com/search?q=bioinformatics%20jobs&amp;src=typd</strong></p>
<p>Find out here about exciting job opportunities in the life sciences.</p>
<blockquote>
<p>Please add well known bioinformatics jobs websites below in comment section.</p>
</blockquote><p>Address of the bookmark: <a href="http://www.nature.com/naturejobs/science/jobs?utf8=%E2%9C%93&amp;q=bioinformatics&amp;where=&amp;commit=Find+Jobs" rel="nofollow">http://www.nature.com/naturejobs/science/jobs?utf8=%E2%9C%93&amp;q=bioinformatics&amp;where=&amp;commit=Find+Jobs</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/36870/understanding-liftover</guid>
	<pubDate>Wed, 06 Jun 2018 10:00:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/36870/understanding-liftover</link>
	<title><![CDATA[Understanding liftOver !]]></title>
	<description><![CDATA[<p>LiftOver is a necesary step to bring all genetical analysis to the same reference build. LiftOver can have three use cases:</p><p>(1) <a href="https://genome.sph.umich.edu/wiki/LiftOver#Lift_genome_positions">Convert genome position from one genome assembly to another genome assembly</a></p><p>In most scenarios, we have known genome positions in NCBI build 36 (UCSC hg 18) and hope to lift them over to NCBI build 37 (UCSC hg19).</p><p>(2) <a href="https://genome.sph.umich.edu/wiki/LiftOver#Lift_dbSNP_rs_numbers">Convert dbSNP rs number from one build to another</a></p><p>(3) <a href="https://genome.sph.umich.edu/wiki/LiftOver#Lift_Merlin.2FPLINK_format">Convert both genome position and dbSNP rs number over different versions</a></p><p>Run:</p><pre>liftOver input.bed hg18ToHg19.over.chain.gz output.bed unlifted.bed</pre><p>The outformat is as follow:</p><pre>Deleted in new:
    Sequence intersects no chains
Partially deleted in new:
    Sequence insufficiently intersects one chain
Split in new:
    Sequence insufficiently intersects multiple chains
Duplicated in new:
    Sequence sufficiently intersects multiple chains
Boundary problem:
    Missing start or end base in an exon</pre><p>For example:</p><p>If you liftOver <span>chr4:6497-6497 from <span>hg19 to GRch38 </span>and it return "deleted in new". </span></p><p>It means chr4:6497-6497 is part of a genomic contig on hg19 that is not anymore mapped on GRch38 because the new assembly is now better built without including this contig.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6561/mathomics-lab</guid>
  <pubDate>Tue, 19 Nov 2013 18:17:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[MATHomics Lab]]></title>
  <description><![CDATA[
<p>Mathomics is a collaborative research group of the Center for Mathematical Modeling and the Center for Genome Regulation at University of Chile, created to play a central role in the development of biotechnological projects, providing state of the art bioinformatics and mathematical modeling tools,  allowing to face these problems from the point of view of Systems Biology. </p>

<p>Lab page @ http://www.mathomics.cl/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6817/research-assistant-university-of-hyderabad</guid>
  <pubDate>Mon, 25 Nov 2013 10:21:26 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Assistant @ University of Hyderabad]]></title>
  <description><![CDATA[
<p>University of Hyderabad<br />Repository for Tomato Genomic Resources<br />Department of Plant Sciences<br />Bioinformatics Position in Tomato Functional Genomics </p>

<p>At the Repository for Tomato Genomics Resources, we are working on Tomato Functional Genomics, using TILLING, Insertional Mutagenesis, proteomics, metabolomics approaches to study fruit ripening in tomato. The current aims of the group include using reverse and forward genetics strategies to isolate tomato mutants delayed in ripening, having high lycopene and folate content in tomato fruits and analysis of light and hormonal signal transduction pathways. For recent publications of the group see (Plant Physiol 161: 2085–2101, Plant Physiol 156: 1424-1438; Molecular Plant 3: 854-869; Plant Methods 6: 3; Plant Methods 5:18; Plant Signaling and Behavior 5:11.).</p>

<p>Currently we have one position available in the projects awarded to Prof. R.P. Sharma funded by Dept of Biotechnology. The qualification for this Position is as follows:</p>

<p>Research Assistant: Applicants should have experience in networking using R language and should be able to develop networks using the transcriptome, proteome and metabolite data sets. M.Tech. in Bioinformatics is required. The selected candidate would be paid Rs. 13,000/-pm- consolidated.</p>

<p>Candidates interested in above positions should send a one page statement clearly explaining how their skills are relevant to the position. The candidates should also enclose detailed CV and the name/email id for three referees. The candidates can send their application by email at rameshwar.sharma@uohyd.ac.in and y.sreelakshmi@uohyd.ac.in on or before December 10th, 2013. The position is purely temporary in nature. Shortlisted candidates would be called for interview. No TA/DA would be provided for attending the interview. We also have openings for CSIR-NET JRF candidates for pursuing PhD in above research areas.</p>

<p>Interested candidates with CSIR-NET JRF can send their CV to the above email<br />addresses.</p>

<p>Advertisement:</p>

<p>http://www.uohyd.ac.in/images/recruitment/tomanet_positions_221113.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43877/crowdgo-machine-learning-and-semantic-similarity-guided-consensus-gene-ontology-annotation</guid>
	<pubDate>Thu, 26 May 2022 00:59:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43877/crowdgo-machine-learning-and-semantic-similarity-guided-consensus-gene-ontology-annotation</link>
	<title><![CDATA[CrowdGO: Machine learning and semantic similarity guided consensus Gene Ontology annotation]]></title>
	<description><![CDATA[<p dir="auto">CrowdGO is a protein Gene Ontology predictor using a meta approach, analyzing the predictions of other tools in order to get an improved precision and recall.</p>
<p dir="auto">Please note that the CrowdGO snakemake workflow is currently only tested on Ubuntu. It should work on OSX, but please report any errors to <a href="mailto:maarten.reijnders@unil.ch">maarten.reijnders@unil.ch</a> or create an issue.</p>
<p>https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010075</p><p>Address of the bookmark: <a href="https://gitlab.com/mreijnders/crowdgo" rel="nofollow">https://gitlab.com/mreijnders/crowdgo</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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