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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/16686?offset=140</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10262/research-fellow-phd-candidate-in-computational-biology-%E2%80%93-2-positions</guid>
  <pubDate>Fri, 25 Apr 2014 20:19:58 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research fellow (PhD candidate) in computational biology – 2 positions]]></title>
  <description><![CDATA[
<p>At the Department of Informatics two 4-year positions as research fellow are available in the field of computational biology connected to the Computational Biology Unit. The positions are linked to the project “Integrated genomics - linking transcriptional and translational regulation over developmental time” supported by the Bergen Research Foundation</p>

<p>The fate of a cell is ultimately the product of the regulation of its genes. Gene regulation is a coordinated process acting at multiple levels of which transcription and translation are the most prominent. The Valen group is dedicated to the fundamental question of how transcription and translation is integrated to obtain the desired protein abundance. The recent development of high-throughput next generation sequencing techniques to monitor both active translation and transcription has made it possible to study this connection at the genome scale.</p>

<p>This project aims to elucidate the links between regulation of translation and transcription. The applicant will analyze next generation sequencing data and model gene regulation on a genome-wide level to identify the features that affect the translational output of transcripts. The work will be done in close collaboration with experimental scientists who will test the predictions of the computational models.</p>

<p>Additional information on the position can be obtained by contacting Eivind Valen (eivind.valen@ii.uib.no).</p>

<p>The research fellow must take part in the University’s approved PhD program leading to the degree within a time limit of 3 years. Application for admission to the PhD program, including a project plan outline for the training module, will be worked out in collaboration with the research group in question.</p>

<p>In total, the fellowship period is 4 years, 25 % of this will be allocated to teaching and/or administrative duties. The fellowship period may be reduced if the successful applicant has held previous employment as a research fellow or similar.</p>

<p>http://www.jobbnorge.no/en/available-jobs/job/102235/research-fellow-phd-candidate-in-computational-biology-2-positions</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14215/the-8000-years-old-tibetian-gene-mutation</guid>
	<pubDate>Wed, 20 Aug 2014 21:57:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14215/the-8000-years-old-tibetian-gene-mutation</link>
	<title><![CDATA[The 8000 years old Tibetian gene mutation !!!]]></title>
	<description><![CDATA[<p>A new study has provided insight into how gene mutation around 8,000 years ago helped Tibetans' to survive in the thin air on the Tibetan Plateau, where an average elevation is of 14,800 feet.<br /><br />A study led by University of Utah scientists is the first to find a genetic cause for the adaptation, a single DNA base pair change that dates back 8,000 years and demonstrate how it contributes to the Tibetans' ability to live in low oxygen conditions.</p><p>About 8,000 years ago, the gene EGLN1 changed by a single DNA base pair. Today, a relatively short time later on the scale of human history, 88 percent of Tibetans have the genetic variation, and it was virtually absent from closely related lowland Asians. The findings indicate the genetic variation endows its carriers with an advantage.<br /><br />In those without the adaptation, low oxygen caused their blood to become thick with oxygen-carrying red blood cells, an attempt to feed starved tissues, which could cause long-term complications such as heart failure. The researchers found that the newly identified genetic variation protected Tibetans by decreasing the over-response to low oxygen.</p><p>Reference: http://www.nature.com/nature/journal/v512/n7513/abs/nature13408.html</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26234/manolis-kellis-lab</guid>
  <pubDate>Sun, 31 Jan 2016 20:51:06 -0600</pubDate>
  <link></link>
  <title><![CDATA[Manolis Kellis Lab]]></title>
  <description><![CDATA[
<p>A major focus of our lab is understanding the effects of genetic variation on molecular phenotypes and human disease. We develop methods for integrating diverse functional genomic datasets of transcription, chromatin modifications, regulator binding, and their changes across multiple conditions to interpret genetic associations, identify causal variants, and predict the effects of genetic perturbations.</p>

<p>More at http://compbio.mit.edu</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28906/gene-finding-and-predictions</guid>
	<pubDate>Fri, 26 Aug 2016 07:26:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28906/gene-finding-and-predictions</link>
	<title><![CDATA[Gene Finding and Predictions]]></title>
	<description><![CDATA[<p><span>In this exercise, a previously annotated gene will be used to measure the accuracy of different gene finding approaches. GRAIL, GENSCAN,&nbsp;</span><tt>geneid</tt><span>, FGENESH, GenomeScan, GrailEXP and GENEWISE will be used to annotate the sequence. Both search by signal, content and homology (protein and cDNA sequences) methods will be employed in order to improve the ab initio results. Weak conservation of Start codons will lead to wrong prediction of initial exons in most cases.</span></p>
<p>http://genome.crg.es/courses/Bioinformatics2003_genefinding/</p><p>Address of the bookmark: <a href="http://genome.crg.es/courses/Bioinformatics2003_genefinding/" rel="nofollow">http://genome.crg.es/courses/Bioinformatics2003_genefinding/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34324/orthognc-a-software-for-accurate-identification-of-orthologs-based-on-gene-neighborhood-conservation</guid>
	<pubDate>Tue, 14 Nov 2017 09:30:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34324/orthognc-a-software-for-accurate-identification-of-orthologs-based-on-gene-neighborhood-conservation</link>
	<title><![CDATA[OrthoGNC: A Software for Accurate Identification of Orthologs Based on Gene Neighborhood Conservation]]></title>
	<description><![CDATA[<div>
<p id="sp0005">Orthology relations can be used to transfer annotations from one gene (or protein) to another. Hence, detecting orthology relations has become an important task in the post-genomic era. Various genomic events, such as duplication and horizontal gene transfer, can cause erroneous assignment of orthology relations. In closely-related species, gene neighborhood information can be used to resolve many ambiguities in orthology inference. Here we present OrthoGNC, a software for accurately predicting pairwise orthology relations based on gene neighborhood conservation. Analyses on simulated and real data reveal the high accuracy of OrthoGNC. In addition to orthology detection, OrthoGNC can be employed to investigate the conservation of genomic context among potential orthologs detected by other methods. OrthoGNC is freely available online at http://bs.ipm.ir/softwares/orthognc and http://tinyurl.com/orthoGNC.</p>
<p>http://www.comp.nus.edu.sg/~wongls/projects/orthoGNC/</p>
</div><p>Address of the bookmark: <a href="http://www.sciencedirect.com/science/article/pii/S1672022917301663" rel="nofollow">http://www.sciencedirect.com/science/article/pii/S1672022917301663</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35252/hgt-finder-a-new-tool-for-horizontal-gene-transfer-finding-and-application-to-aspergillus-genomes</guid>
	<pubDate>Wed, 17 Jan 2018 05:03:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35252/hgt-finder-a-new-tool-for-horizontal-gene-transfer-finding-and-application-to-aspergillus-genomes</link>
	<title><![CDATA[HGT-Finder: A New Tool for Horizontal Gene Transfer Finding and Application to Aspergillus genomes]]></title>
	<description><![CDATA[<p><span>HGT-Finder: </span></p>
<p><span>(i) can be used for HGT detection in both prokaryotes and eukaryotes, </span></p>
<p><span>(ii) can report a statistical&nbsp;</span><em>P</em><span>&nbsp;value for each gene to indicate how likely it is to be horizontally transferred, and </span></p>
<p><span>(iii) is fully automated (requires minimal human intervention), as well as very easy to install and run.&nbsp;</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4626719/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4626719/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37954/biogps-spotlight-on-the-gene-expression-atlas</guid>
	<pubDate>Thu, 18 Oct 2018 12:15:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37954/biogps-spotlight-on-the-gene-expression-atlas</link>
	<title><![CDATA[BioGPS: Spotlight on the Gene Expression Atlas]]></title>
	<description><![CDATA[<p>BioGPS opened 2016 with a publication in Nucleic Acids Research, right after the New Year holiday. Throughout the year, new designs for the site were being created, reviewed, adjusted, reviewed, adjusted, and more review/adjustments in anticipation of a site redesign for 2017. A Plugin registration Blitz was held in March and April; followed by a Plugin Review Blitz in May. The BioGPS spotlight series was also restarted, with spotlights on BGEE, Intermine, and other Intermine-related plugins.</p>
<p>There were ~910,000 requests made to BioGPS in 2016. Requests to BioGPS peaked in March and at the lowest in December.</p><p>Address of the bookmark: <a href="http://biogps.org/" rel="nofollow">http://biogps.org/</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/43804/agora-algorithm-for-gene-order-reconstruction-in-ancestors</guid>
	<pubDate>Mon, 28 Feb 2022 23:26:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43804/agora-algorithm-for-gene-order-reconstruction-in-ancestors</link>
	<title><![CDATA[AGORA: Algorithm for Gene Order Reconstruction in Ancestors]]></title>
	<description><![CDATA[<p dir="auto">AGORA stands for &ldquo;Algorithm for Gene Order Reconstruction in Ancestors&rdquo; and was developed by Matthieu Muffato in the DYOGEN Laboratory at the &Eacute;cole normale sup&eacute;rieure in Paris in 2008.</p>
<div>
<pre><code>    // | |     //   ) )  //   ) ) //   ) )  // | |
   //__| |    //        //   / / //___/ /  //__| |
  / ___  |   //  ____  //   / / / ___ (   / ___  |
 //    | |  //    / / //   / / //   | |  //    | |
//     | | ((____/ / ((___/ / //    | | //     | |
</code></pre>
</div>
<p dir="auto">AGORA is used to generate ancestral genomes for the&nbsp;<a href="https://www.genomicus.biologie.ens.fr/genomicus">Genomicus</a>&nbsp;online server for gene order comparison, and has been in constant use in the group since.</p><p>Address of the bookmark: <a href="https://github.com/DyogenIBENS/Agora" rel="nofollow">https://github.com/DyogenIBENS/Agora</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36849/glean-an-unsupervised-learning-system-to-integrate-disparate-sources-of-gene-structure-evidence</guid>
	<pubDate>Sat, 02 Jun 2018 07:38:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36849/glean-an-unsupervised-learning-system-to-integrate-disparate-sources-of-gene-structure-evidence</link>
	<title><![CDATA[GLEAN: an unsupervised learning system to integrate disparate sources of gene structure evidence]]></title>
	<description><![CDATA[<p><span>GLEAN is an unsupervised learning system to integrate disparate sources of gene structure evidence (gene model predictions, EST/protein genomic sequence alignments, SAGE/peptide tags, etc) to produce a consensus gene prediction, without prior training.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/glean-gene/" rel="nofollow">https://sourceforge.net/projects/glean-gene/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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