<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26303?offset=1410</link>
	<atom:link href="https://bioinformaticsonline.com/related/26303?offset=1410" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/6052/university-of-california-irvine-center-for-complex-biological-systems</guid>
	<pubDate>Mon, 04 Nov 2013 17:10:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/6052/university-of-california-irvine-center-for-complex-biological-systems</link>
	<title><![CDATA[University of California, Irvine - Center for Complex Biological Systems]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/chPJ6OdVl4o" frameborder="0" allowfullscreen></iframe>The University of California Irvine's Center for Complex Biological Systems got its start just as there was a revolution in biology. Systems Biology requires that scientists work across many disciplines including engineering, physics and mathematics. The Center specializes in helping form the kinds of teams that will propel biological research into the future. It is also proud to be able to train students in the new interdisciplinary approach.

http://ccbs.uci.edu]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7569/phd-at-university-of-calgary</guid>
  <pubDate>Fri, 27 Dec 2013 20:24:39 -0600</pubDate>
  <link></link>
  <title><![CDATA[PhD at University of Calgary]]></title>
  <description><![CDATA[
<p>Institution/Company: <br />University of Calgary<br />Location: <br />Calgary, AB<br />Job Description: </p>

<p>Novel diagnostic platform for detection of Osteoarthritis</p>

<p>I invite applications from highly motivated individuals to join my laboratory as a PhD student in Systems Biology at the University of Calgary McCaig Institute for Bone and Joint Health. This project is aimed at characterizing the networks of physical (protein-protein) interactions underlying inflammatory processes in patients with Osteoarthritis and how this differs from patients with Rheumatoid Arthritis and normal individuals. This work will eventually lead to the development of a novel diagnostic platform for the non-invasive and accurate detection of early Osteoarthritis. The selected candidate will use state-of-the-art computational methodologies to systematically analyze proteomic data, and develop /implement new algorithms to identify protein and functional interaction networks from high throughput experimental data. The individual will also benefit by working closely with experts at the UofC and UofA through an AIHS Alberta Osteoarthritis Team Grant which includes experts from all pillars of health research. The candidate will also be supported to attend bioinformatics workshops and conferences to advance and disseminate their research.<br />Qualifications: The ideal candidate will have a Master’s degree in Computational Biology, Bioinformatics, or equivalent with strong background knowledge of the Biological Sciences, Biochemistry, and Microbiology. The individual should additionally have experience in handling high-throughput data sets as well as programming skills. The candidate will be registered as a PhD student in Dr. Krawetz’s laboratory, located in the new state-of-the-art Health Research Innovation Centre at the UofC. The individual will have strong verbal and written skills and the ability to work efficiently in a team environment.</p>

<p>In addition to the outstanding research opportunities available in this setting, students also enjoy the many cultural and sporting amenities provided in the city of Calgary, and can take advantage of the unparalleled skiing and hiking in the Rocky Mountains that are less than an hour away.</p>

<p>Candidates must be academically competitive and will be expected to apply for external funding. The stipend is $25,000/yr. For outstanding PhD students, internal top-up award opportunities are available on a competitive basis. If interested in joining the lab, please contact Dr. Krawetz directly at rkrawetz@ucalgary.ca and provide the following information:</p>

<p>- Short cover letter explaining your interest in the lab<br />- Resume<br />- Scanned copy of transcript or listing of course grades<br />- Names and contact information for two individuals who will be willing to provide letters of reference</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4550/gupta-lab</guid>
  <pubDate>Sun, 15 Sep 2013 09:31:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Gupta Lab]]></title>
  <description><![CDATA[
<p>Gupta laboratory of Natural Information Processing at DA-IICT. Research in our lab currently focuses on two aspects of information processing viz. deciphering the information processing principles in life (systems biology) and making a computer out of bio-molecules. The key expertise of the lab is in error-correcting codes. We also work in classical and quantum information processing principles with expertise in coding theory and its wide variety of applications in Information and Communication Technology (ICT). </p>

<p>More @ http://www.guptalab.org/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7383/embo-practical-course-on-bioinformatics-and-genomes-analyses-at-hellenic-pasteur-institute-athens-greece</guid>
  <pubDate>Sat, 21 Dec 2013 10:00:24 -0600</pubDate>
  <link></link>
  <title><![CDATA[EMBO practical Course on  "Bioinformatics and Genomes Analyses" at Hellenic Pasteur Institute, Athens, Greece]]></title>
  <description><![CDATA[
<p>The main objectives of this Practical Course are to strengthen skills <br />of PhD students and young researchers in the domain of Bioinformatics <br />and Genome Data Analyses on the use of advanced fundamental algorithms <br />and their applications in genome studies.</p>

<p>The course topics will include theoretical and practical aspects in:<br />- Genomes comparisons,<br />- Evolutionary analyses (orthologs, paralogs and ancestral genomes <br />inference),<br />- RNAseq and Next Generation Sequencing (including algorithms, methods <br />and sequence mapping tools, data analyses and applications).</p>

<p>The course programme will be centred on theoretical presentations <br />followed by practical sessions. Practical sessions in a Linux <br />environment will involve Unix shell and Perl scripting. Participants <br />are assumed to be familiar with this environment.</p>

<p>A series of lectures delivered by prominent scientists on recent hot <br />topics in genome (Viruses, Prokaryotes, Eukaryotes) studies will be <br />included in the programme and future research perspectives will be <br />highlighted.</p>

<p>The topics that will be included in the course programme are similar <br />to those included in previously organized courses:http://www.pasteur.fr/~tekaia/BGA_courses.html</p>

<p>The course is aimed at motivated Ph.D students and Post-Doctoral <br />Researchers in Academic Institutions, with background in Mathematics, <br />Statistics, Biology or Computer Science and who are involved in <br />Bioinformatics and Genomes studies.</p>

<p>Selection of participants will be based on their background, running <br />research projects and on expressed motivations.<br />Selected students will have free accommodation and meals and are <br />expected to contribute with 200 euros and to pay for their travel <br />expenses.<br />All participants (students and invited speakers) will stay in the same <br />hotel.</p>

<p>Detailed indications are available on the course web site: http://events.embo.org/14-comparative-genomics/index.html</p>

<p>Candidates are advised to complete carefully the application form, <br />together with an abstract of at least one of their running projects, a <br />"one-page CV" and a personal Identity Picture (Photo).</p>

<p>The application deadline is March 14, 2014.</p>

<p>The organizers:<br />Menelaos Manoussakis, Hellenic Pasteur Institute, Athens, Greece.<br />Evdokia Karagouni, Hellenic Pasteur Institute, Athens - Greece.<br />Evie Melanitou,  Institut Pasteur Paris - France.<br />Fredj Tekaia ( Institut Pasteur Paris France)<br />URL: http://www.pasteur.fr/~tekaia/BGA_courses.html</p>

<p>Date: 5 – 17 May, 2014. <br />More at http://events.embo.org/14-comparative-genomics/index.html<br />will take place in the ,</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/43001/gamper-lab</guid>
  <pubDate>Fri, 26 Mar 2021 07:45:02 -0500</pubDate>
  <link></link>
  <title><![CDATA[Gamper Lab]]></title>
  <description><![CDATA[
<p>Lab focuses on examining the mechanisms governing the signalling pathways from DNA damage sensing to the activation of stress-response genes. The long-term goal is to find proteins that are drug targets for cancer treatment (such as radiosensitizers for radiation therapy) or biomarkers that increase the predictive value of therapeutic outcome.</p>

<p>https://amgamper.weebly.com/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</guid>
	<pubDate>Fri, 27 Dec 2013 19:58:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</link>
	<title><![CDATA[Oldest Hominin DNA Sequenced]]></title>
	<description><![CDATA[<p>Matthias Meyer and his team from the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, have developed new techniques for retrieving and sequencing highly degraded ancient DNA. They then joined forces with Juan-Luis Arsuaga and applied the new techniques to a cave bear from the Sima de los Huesos site. After this success, the researchers sampled two grams of bone powder from a hominin thigh bone from the cave. They extracted its DNA and sequenced the genome of the mitochondria or mtDNA, a small part of the genome that is passed down along the maternal line and occurs in many copies per cell. The researchers then compared this ancient mitochondrial DNA with Neandertals, Denisovans, present-day humans, and apes.<br /><br />From the missing mutations in the old DNA sequences the researchers calculated that the Sima hominin lived about 400,000 years ago. They also found that it shared a common ancestor with the Denisovans, an extinct archaic group from Asia related to the Neandertals, about 700,000 years ago. "The fact that the mtDNA of the Sima de los Huesos hominin shares a common ancestor with Denisovan rather than Neandertal mtDNAs is unexpected since its skeletal remains carry Neandertal-derived features," says Matthias Meyer. Considering their age and Neandertal-like features, the Sima hominins were likely related to the population ancestral to both Neandertals and Denisovans. Another possibility is that gene flow from yet another group of hominins brought the Denisova-like mtDNA into the Sima hominins or their ancestors.<br /><br /></p><p>Reference</p><p>http://www.sciencedaily.com/releases/2013/12/131204132018.htm</p>]]></description>
	<dc:creator>Surajeet</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4107/natasa-przulj-lab</guid>
  <pubDate>Fri, 30 Aug 2013 06:29:17 -0500</pubDate>
  <link></link>
  <title><![CDATA[Nataša Pržulj Lab]]></title>
  <description><![CDATA[
<p>Nataša Pržulj Lab's research involves applications of graph theory, mathematical modeling, and computational techniques to solving large-scale problems in computational and systems biology.They are interested in computational and theoretical solutions to practical problems in many areas of systems biology, planar cell polarity, proteomics, cancer informatics, and drug discovery and design.</p>

<p>More at http://www.doc.ic.ac.uk/~natasha/index.html</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/7986/list-of-bioinformatics-open-source-projectssoftware</guid>
	<pubDate>Tue, 21 Jan 2014 14:28:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/7986/list-of-bioinformatics-open-source-projectssoftware</link>
	<title><![CDATA[List of bioinformatics open source projects/software.]]></title>
	<description><![CDATA[<p>Open source software is software that can be freely used, changed, and shared (in modified or unmodified form) by anyone. Open source software is made by many people, and distributed under licenses that comply with the Open Source Definition.The Open Source Initiative (OSI) is a global non-profit that supports and promotes the open source movement. Followings are the OS bioinformatics projects/software :</p><p><strong>.NET Bio</strong></p><p>http://blogs.msdn.com/b/msr_er/archive/2011/10/18/microsoft-biology-foundation-evolves-into-new-toolkit-net-bio.aspx</p><p>A language-neutral bioinformatics toolkit built using the Microsoft 4.0 .NET Framework to help developers, researchers, and scientists.</p><p><strong>AMPHORA</strong> ("AutoMated Phylogenomic infeRence Application")</p><p>http://wolbachia.biology.virginia.edu/WuLab/Software.html</p><p><a href="http://en.wikipedia.org/wiki/Metagenomics" title="Metagenomics">Metagenomics</a> analysis software</p><p><strong>Anduril</strong></p><p>http://www.anduril.org/anduril/site/</p><p>Component-based <a href="http://en.wikipedia.org/wiki/Workflow" title="Workflow">workflow</a> framework for data analysis</p><p>Armadillo workflow platform</p><p>Tool for designing and executing phylogenetic workflows</p><p><strong>AutoDock</strong></p><p>http://autodock.scripps.edu/</p><p>suite of automated docking tools</p><p><strong>Biochemical Algorithms Library (BALL)</strong></p><p>http://www.ball-project.org/</p><p>C++ library and framework for molecular modeling and visualization designed for rapid prototyping</p><p><strong>Bio4j</strong></p><p>http://bio4j.com/</p><p>Bio4j is a <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">bioinformatics</a> platform and <a href="http://en.wikipedia.org/wiki/Chart" title="Chart">graph</a> based <a href="http://en.wikipedia.org/wiki/Database" title="Database">database</a> built around most data available in <a href="http://en.wikipedia.org/wiki/UniProt" title="UniProt">UniProt</a> KB(<a href="http://en.wikipedia.org/wiki/Swiss-Prot" title="Swiss-Prot">Swiss-Prot</a> + <a href="http://en.wikipedia.org/wiki/TrEMBL" title="TrEMBL">TrEMBL</a>), <a href="http://en.wikipedia.org/wiki/Gene_Ontology" title="Gene Ontology">Gene Ontology</a> (GO), <a href="http://en.wikipedia.org/w/index.php?title=UniRef&amp;action=edit&amp;redlink=1" title="UniRef (page does not exist)">UniRef</a> (50,90,100), <a href="http://en.wikipedia.org/wiki/RefSeq" title="RefSeq">RefSeq</a>, <a href="http://en.wikipedia.org/wiki/National_Center_for_Biotechnology_Information" title="National Center for Biotechnology Information">NCBI</a> taxonomy, and Expasy Enzyme DB</p><p><strong>Bioclipse</strong></p><p>www.bioclipse.net</p><p>Visual platform for <a href="http://en.wikipedia.org/wiki/Cheminformatics" title="Cheminformatics">chemo</a>- and <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">bioinformatics</a> based on the <a href="http://en.wikipedia.org/wiki/Eclipse_%28software%29" title="Eclipse (software)">Eclipse</a> Rich Client Platform (RCP).</p><p><strong>Bioconductor</strong></p><p>http://www.bioconductor.org/</p><p><a href="http://en.wikipedia.org/wiki/R_%28programming_language%29" title="R (programming language)">R (programming language)</a> language toolkit</p><p><strong>Bioinformatics Learning Tutorial (BLT)</strong></p><p>http://sourceforge.net/projects/biotutorial/</p><p>Educational <a href="http://en.wikipedia.org/wiki/Interactive_tutorials" title="Interactive tutorials">interactive tutorials</a> and 3D animations for Replication, Transcription, and Translation</p><p><strong>BioHaskell</strong></p><p>http://biohaskell.org/</p><p><a href="http://en.wikipedia.org/wiki/Haskell_%28programming_language%29" title="Haskell (programming language)">Haskell (programming language)</a></p><p><strong>BioJava</strong></p><p>http://biojava.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Java_%28programming_language%29" title="Java (programming language)">Java (programming language)</a></p><p><strong>BioMOBY</strong></p><p>http://biomoby.org/</p><p>registry of <a href="http://en.wikipedia.org/wiki/Web_services" title="Web services">web services</a></p><p><strong>BioPerl</strong></p><p>http://www.bioperl.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Perl" title="Perl">Perl</a> language toolkit</p><p><strong>BioPHP</strong></p><p>http://www.biophp.org/</p><p><a href="http://en.wikipedia.org/wiki/PHP" title="PHP">PHP</a> language toolkit</p><p><strong>Biopython</strong></p><p>http://biopython.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Python_%28programming_language%29" title="Python (programming language)">Python</a> language toolkit</p><p><strong>BioRails</strong></p><p>https://github.com/biorails</p><p>a <a href="http://en.wikipedia.org/wiki/Data_management_system" title="Data management system">data management system</a> designed to support researchers in <a href="http://en.wikipedia.org/wiki/Drug_discovery" title="Drug discovery">drug discovery</a></p><p><strong>BioRuby</strong></p><p>http://bioruby.org/</p><p><a href="http://en.wikipedia.org/wiki/Ruby_%28programming_language%29" title="Ruby (programming language)">Ruby</a> language toolkit</p><p><strong>BioSmalltalk</strong></p><p>https://code.google.com/p/biosmalltalk/</p><p><a href="http://en.wikipedia.org/wiki/Smalltalk_%28programming_language%29" title="Smalltalk (programming language)">Smalltalk</a> language toolkit</p><p><strong>BioUno</strong></p><p>http://www.biouno.org/</p><p><a href="http://en.wikipedia.org/w/index.php?title=BioUno&amp;action=edit&amp;redlink=1" title="BioUno (page does not exist)">BioUno</a> is a project that applies <a href="http://en.wikipedia.org/wiki/Continuous_Integration" title="Continuous Integration">Continuous Integration</a> tools and techniques in <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">Bioinformatics</a>. It uses <a href="http://en.wikipedia.org/wiki/Jenkins_%28software%29" title="Jenkins (software)">Jenkins</a> and its plug-in API to create <a href="http://en.wikipedia.org/wiki/Bioinformatics_workflow_management_system" title="Bioinformatics workflow management system">biology workflows</a> and manage <a href="http://en.wikipedia.org/wiki/Computer_clusters" title="Computer clusters">computer clusters</a>.</p><p><strong>caCORE</strong></p><p>&nbsp;</p><p>ontologic representation environment</p><p><strong>caArray</strong></p><p>https://cabig-stage.nci.nih.gov/community/tools/caArray</p><p>ontologic representation environment</p><p><strong>EMBOSS</strong></p><p>http://emboss.sourceforge.net/</p><p>Suite of packages for sequencing, searching, etc.</p><p><strong>Gaggle</strong></p><p>https://www.gaggle.net/</p><p>A framework for interoperability between systems biology software</p><p><strong>Galaxy</strong></p><p>http://galaxyproject.org/</p><p><a href="http://en.wikipedia.org/wiki/Scientific_workflow_system" title="Scientific workflow system">Scientific workflow</a> and <a href="http://en.wikipedia.org/wiki/Data_integration" title="Data integration">data integration</a> system</p><p><strong>GenePattern</strong></p><p>http://www.broadinstitute.org/cancer/software/genepattern/</p><p><a href="http://en.wikipedia.org/wiki/Scientific_workflow_system" title="Scientific workflow system">Scientific workflow system</a> that provides access to more than 150 genomic analysis tools</p><p><strong>GeWorkbench</strong></p><p>http://wiki.c2b2.columbia.edu/workbench/index.php/Home</p><p>Genomic <a href="http://en.wikipedia.org/wiki/Data_integration" title="Data integration">data integration</a> platform</p><p><strong>GMOD</strong></p><p>http://www.gmod.org/wiki/Main_Page</p><p>Toolkit for addressing many common challenges at biological databases.</p><p><strong>GeneProf</strong></p><p>http://www.geneprof.org/GeneProf/</p><p>A web-based, bioinformatics software suite for the analysis of functional genomics experiments, e.g. RNA-seq or ChIP-seq.</p><p><strong>GeneTalk</strong></p><p>http://www.gene-talk.de/</p><p>Tool for filtering sequence variants in <a href="http://en.wikipedia.org/wiki/Variant_Call_Format" title="Variant Call Format">VCF</a> files. Network for scientists and clinicians for expertise and knowledge exchange. Database of annotations aboute sequence variants with clinically relevant information.</p><p><strong>GenGIS</strong></p><p>http://kiwi.cs.dal.ca/GenGIS/Main_Page</p><p>Application that allows users to combine digital map data with information about biological sequences collected from the environment.</p><p><strong>GenomeSpace</strong></p><p>http://www.genomespace.org/</p><p>Centralized web application that provides data format transformations and facilitates connections with other bioinformatics tools</p><p><strong>GENtle</strong></p><p>http://directory.fsf.org/wiki/GENtle</p><p>An equivalent to the proprietary <a href="http://en.wikipedia.org/wiki/Vector_NTI" title="Vector NTI">Vector NTI</a>, a tool to analyze and edit <a href="http://en.wikipedia.org/wiki/DNA" title="DNA">DNA</a> sequence files</p><p><strong>Integrated Genome Browser</strong></p><p>http://bioviz.org/igb/</p><p><a href="http://en.wikipedia.org/wiki/Java_%28software_platform%29" title="Java (software platform)">Java</a>-based desktop <a href="http://en.wikipedia.org/wiki/Genome_browser" title="Genome browser">genome browser</a></p><p><strong>Integrative Genomics Viewer (IGV)</strong></p><p>http://www.broadinstitute.org/igv/</p><p>High-performance desktop tool for interactive visual exploration of diverse genomic data</p><p><strong>IntAct</strong></p><p>http://www.ebi.ac.uk/intact/</p><p>molecular interaction database</p><p><strong>InterMine</strong></p><p>http://intermine.github.io/intermine.org/</p><p>Extensive data warehouse system for the analysis and integration of biological datasets</p><p><strong>Java Treeview</strong></p><p>http://jtreeview.sourceforge.net/</p><p>microarray data viewer</p><p><strong>LabKey Server</strong></p><p>http://labkey.com/</p><p>platform for integrating, analyzing and sharing data</p><p><strong>OpenClinica</strong></p><p>https://www.openclinica.com/</p><p>software for capturing and managing data in clinical trials</p><p><a href="http://www.biomedcentral.com/1471-2164/13/512">PromKappa</a></p><p>http://xbioinformatics.wordpress.com/tag/promkappa/</p><p>PromKappa (Promoter analysis by Kappa) software program used for promoter pattern generation and promoter analysis.</p><p><strong>MeV: Multi-Experiment Viewer</strong></p><p>http://www.tm4.org/mev.html</p><p>a desktop application for the analysis, visualization and data-mining of large-scale genomic data</p><p><strong>PathVisio</strong></p><p>http://www.pathvisio.org/</p><p>a desktop software for drawing, analysis and visualization of biological pathways</p><p>REDCRAFT</p><p>software for determining tertiary protein structure given assigned Residual Dipolar Coupling data</p><p>SAM Tools</p><p>Data format (SAM) and accompanying tool suite, for storing large nucleotide sequence alignments</p><p><a href="http://en.wikipedia.org/wiki/Staden_Package" title="Staden Package">Staden Package</a></p><p>Sequence assembly, editing and analysis, primarily consisting of gap4, gap5 and spin.</p><p><a href="http://en.wikipedia.org/wiki/STAMP" title="STAMP">STAMP</a></p><p>Software package for analyzing metagenomic profiles that promotes &lsquo;best practices&rsquo; in choosing appropriate statistical techniques and reporting results.</p><p><a href="http://supfam.org/supraHex">supraHex</a></p><p>An open-source R/Bioconductor package for omics data analysis using a supra-hexagonal map</p><p><a href="http://en.wikipedia.org/wiki/Taverna_workbench" title="Taverna workbench">Taverna workbench</a></p><p>Tool for designing and executing workflows</p><p>TGAC Browser</p><p>Genome Browser, visualisation solutions for big data in the genomic era</p><p>T-REX WebServer</p><p>Bioinformatics and phylogenetics webserver (NJ, PhyML, RAxML, MAFFT, MUSCLE, Newick viewer, <a href="http://en.wikipedia.org/wiki/Horizontal_gene_transfer" title="Horizontal gene transfer">Horizontal gene transfer</a> detection, Reticulograms, Substitution models)</p><p><a href="http://en.wikipedia.org/wiki/UGENE" title="UGENE">UGENE</a></p><p>integrated bioinformatics tools</p><p>Visomics</p><p>bioinformatics tools for omics data</p><p>Genome Analysis Toolkit 1.0 (GATK 1.0)</p><p>a software package to analyse next-generation resequencing data</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24984/ra-bioinformatics-at-nii</guid>
  <pubDate>Thu, 22 Oct 2015 01:56:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at NII]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF IMMUNOLOGY</p>

<p>NEW DELHI-110067</p>

<p>Applications are invited for the position of Research Associate (RA) for the following time-bound sponsored project as per the details given below:</p>

<p>1. BTIS project entitled, “National Infrastructural Facility in the Area of Immunology” funded by DBT</p>

<p>Research Associate (One Position only)</p>

<p>Dr. Debasisa Mohanty Staff Scientist-VI deb@nii.res.in</p>

<p>Educational Qualifications: Ph.D in Bioinformatics or Biological Sciences or Biotechnology with research experience and publication record in indexed peer reviewed journals in the area of bioinformatics or computational biology.</p>

<p>Emoluments: The selected candidates will draw consolidated emoluments as per Institute Rules, depending upon qualifications &amp; experience Research Associate: Rs. 36,000/- per month plus 30% HRA</p>

<p>Job description &amp; Desired Knowledge: The candidate should be well versed in Programming in PERL/C++, HTML, CGI, web sever and portal development, computational analysis of protein structure &amp; function, molecular dynamics simulations and use of high performance computing systems.</p>

<p>General Terms &amp; Conditions:-</p>

<p>1. The candidates selected for the above posts will be on contract for one year or duration of the project whichever is shorter, at a time.</p>

<p>2. No hostel/ housing facility will be provided.</p>

<p>3. Applicants may clearly mention the category they belong to i.e. SC/ST/OBC/PH and attach documentary proof of the same.</p>

<p>4. No TA/DA will be paid for attending the interview, if called for.</p>

<p>5. Apart from sending application in the prescribed format given below, candidates should send complete Curriculum Vitae along with the names of three referees. Curriculum Vitae should contain details of the experimental expertise and list of publications. 6. Canvassing in any form will be a disqualification.</p>

<p>HOW TO APPLY Interested candidates may apply directly, STRICTLY IN THE PRESCRIBED FORMAT GIVEN BELOW, through e-mail, to the Investigator of the project, clearly indicating the name of the project along with their complete C.V., Email ID, fax numbers, telephone numbers. Only Short listed candidates will be called for interview and they required to submit attested copies of all their certificates and a Demand Draft of Rs 100/- drawn on Canara Bank or Indian Bank payable at Delhi/New Delhi in favour of the Director, NII (SC/ST/PH and Women candidates are exempted from payment of fees) subject to submission of documentary proof), at the time of interview. (E-MAIL APPLICATIONS SHOULD MENTION BTIS-RA 2015 IN THE SUBJECT LINE)</p>

<p>LAST DATE OF RECEIPT OF APPLICATIONS: 29th October, 2015</p>

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<p>www1.nii.res.in/sites/default/files/projectappointments-Dr.Mohanty-29oct2015.pdf</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42987/public-databases-for-bioinformatics</guid>
	<pubDate>Tue, 23 Mar 2021 05:32:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42987/public-databases-for-bioinformatics</link>
	<title><![CDATA[Public Databases for Bioinformatics !]]></title>
	<description><![CDATA[<pre>https://www.nature.com/articles/s41467-020-17155-y<br><br>Server Infrastructure:

File Server:

dhara: Synology 3614 Storage Appliance
4 Core Xeon
108TB disk storage
10Gb ethernet to SCG3
Access atx: dhara:5000
Has btsync server (try it - its much better than dropbox)

Compute Servers:

nandi: Kundaje and Phi Server
24 intel cores
256GB RAM
500GB of SSD storage 
36TB RAID6 local storage
4 Intel Phi's (space for 4 more GPU's)


durga: Montgomery and sensitive data
24 intel cores
256GB RAM
500GB of SSD RAID0 storage 
60TB RAID6 local storage

mitra: Bassik and Web/DB Server
24 core
256GB RAM 
500GB of SSD RAID0 storage 
36TB RAID6 local storage

vayu: Kundaje GPU server
4 core
64GB RAM 
200GB of SSD storage 
8TB RAID10 local storage
4 Nvidia GTX 970 4GB GPUs

amold: Bickel and SGE server
32 AMD core
128GB RAM 
200GB of SSD storage 
12TB RAID5 local storage

wotan: Bickel and SGE server
64 AMD core
256GB RAM 
200GB of SSD storage 
12TB RAID5 local storage

Filesystem:

/users/$USER
default home directory
full backups nightly 
nfs mount to dhara
should store code, papers, and other highly processed data here

/mnt/data/
globally accessible data
should store common data here
e.g. genomes and indexes, annotations, ENCODE data  
if you dont want this to count towards your quote you must chown

/mnt/lab_data/$LAB/
lab accessible data
should store lab project data here 
e.g. ATAC-seq prediction data, enhancer prediction, motif calls

/srv/scratch/$USER
fast local storage
not backed up, but on raid and data will never be deleted
most analysis should be performed here

/srv/persistent/$USER
fast local storage
synced nightly, but not backed up
       ie if the hard drives fail or you delete something and notice 
       within 24 hours we can recover. Otherwise not. (vs home which is 
       properly backed up )  
intermediate analysis products that would be hard to recover should be stored here 
       e.g. stochastic analysis results that need to be kept so that paper 
       results can be reproduced

/srv/www/$LABNAME/
web accessible from mitra.stanford.edu
*NOT BACKED UP*

Some parallel programming patterns:

# gzip a bunch of files
parallel gzip -- *.FILESTOGZIP

# fork example in python:
(for more detailed examples look at 
 https://github.com/nboley/grit/ grit/lib/multiprocessing_utils.py)

import os
import time
import random

import multiprocessing

class ProcessSafeOPStream( object ):
    def __init__( self, writeable_obj ):
        self.writeable_obj = writeable_obj
        self.lock = multiprocessing.Lock()
        self.name = self.writeable_obj.name
        return
    
    def write( self, data ):
        self.lock.acquire()
        self.writeable_obj.write( data )
        self.writeable_obj.flush()
        self.lock.release()
        return
    
    def close( self ):
        self.writeable_obj.close()

def worker(queue, ofp):
    # Try without this
    random.seed()
    while True:
        i = queue.get()
        if i == 'FINISHED': return
        # simulate an expensive function
        x = random.random()
        time.sleep(x/10)
        print i, x
        ofp.write("%i\t%s\n" % (i, x))

NSIMS = 10000
NPROC = 25

# populate queue
todo = multiprocessing.Queue()
for i in xrange(NSIMS): todo.put(i)
for i in xrange(NPROC): todo.put('FINISHED')

ofp = ProcessSafeOPStream( open("output.txt", "w") )

pids = []
for i in xrange(NPROC):
    pid = os.fork()
    if pid == 0:
       worker(todo, ofp)
       os._exit(0)
    else:
       pids.append(pid)  

for pid in pids:
    os.waitpid(pid, 0)

ofp.close()

print "FINISHED"<br><br></pre>
<p>For use case 1 we obtained the following ENCODE and ROADMAP datasets&nbsp;<a href="https://www.encodeproject.org/files/ENCFF446WOD/@@download/ENCFF446WOD.bed.gz">https://www.encodeproject.org/files/ENCFF446WOD/@@download/ENCFF446WOD.bed.gz</a>,&nbsp;<a href="https://www.encodeproject.org/files/ENCFF546PJU/@@download/ENCFF546PJU.bam">https://www.encodeproject.org/files/ENCFF546PJU/@@download/ENCFF546PJU.bam</a>,&nbsp;<a href="https://www.encodeproject.org/files/ENCFF059BEU/@@download/ENCFF059BEU.bam">https://www.encodeproject.org/files/ENCFF059BEU/@@download/ENCFF059BEU.bam</a>. Blacklisted regions were obtained from&nbsp;<a href="http://mitra.stanford.edu/kundaje/akundaje/release/blacklists/hg38-human/hg38.blacklist.bed.gz">http://mitra.stanford.edu/kundaje/akundaje/release/blacklists/hg38-human/hg38.blacklist.bed.gz</a>. The human genome version hg38 was obtained from&nbsp;<a href="http://hgdownload.cse.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz">http://hgdownload.cse.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz</a>.</p>
<p>For use case 2 we used the set of narrowPeak files summarized in&nbsp;<a href="https://github.com/wkopp/janggu_usecases/tree/master/extra/urls.txt">https://github.com/wkopp/janggu_usecases/tree/master/extra/urls.txt</a>&nbsp;(archived version v1.0.1). The human genome version hg19 was obtained from&nbsp;<a href="http://hgdownload.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz">http://hgdownload.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz</a></p>
<p>For use case 3 we used the ENCODE datasets&nbsp;<a href="https://www.encodeproject.org/files/ENCFF591XCX/@@download/ENCFF591XCX.bam">https://www.encodeproject.org/files/ENCFF591XCX/@@download/ENCFF591XCX.bam</a>,&nbsp;<a href="https://www.encodeproject.org/files/ENCFF736LHE/@@download/ENCFF736LHE.bigWig">https://www.encodeproject.org/files/ENCFF736LHE/@@download/ENCFF736LHE.bigWig</a>,&nbsp;<a href="https://www.encodeproject.org/files/ENCFF177HHM/@@download/ENCFF177HHM.bam">https://www.encodeproject.org/files/ENCFF177HHM/@@download/ENCFF177HHM.bam</a>&nbsp;as we as the GENCODE annotation v29 from&nbsp;<a href="ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_29/gencode.v29.annotation.gtf.gz">ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_29/gencode.v29.annotation.gtf.gz</a>.</p><p>Address of the bookmark: <a href="http://mitra.stanford.edu/" rel="nofollow">http://mitra.stanford.edu/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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