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	<link>https://bioinformaticsonline.com/related/30654?offset=70</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32154/decostar-detection-of-co-evolution</guid>
	<pubDate>Fri, 14 Apr 2017 06:27:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32154/decostar-detection-of-co-evolution</link>
	<title><![CDATA[DeCoSTAR - Detection of Co-evolution]]></title>
	<description><![CDATA[<p><span>DeCoSTAR is a software which aims at reconstructing ancestral gene or genome organizations, in the form of sets of neighborhood relations -adjacencies- between pairs of ancestral genes or gene domains.</span><br><span>Ancestral genes or domains are deduced from reconciled gene trees in a context of birth, speciation, duplication, loss, transfer, which are either given as input or computed with the&nbsp;</span><a href="http://mbb.univ-montp2.fr/MBB/download_sources/16__TERA">ecceTERA package</a><span>, to which DeCoSTAR is integrated. DeCoSTAR constructs parsimonious scenarios of gains and breakages of adjacencies, and contains in particular all the features of previous software DeCo, DeCoLT, ArtDeCo and DeClone. It provides statistical supports on ancestral adjacencies, or the possibility to handle badly assembled genomes.&nbsp;</span><br><span>DeCoSTAR is able to reconstruct the histories of domains inside genes, including gene fusion and fission events, as well as ancestral genome structures for dozens of whole genomes from all kingdoms of life in a few minutes.</span></p><p>Address of the bookmark: <a href="http://pbil.univ-lyon1.fr/software/DeCoSTAR/" rel="nofollow">http://pbil.univ-lyon1.fr/software/DeCoSTAR/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/842/ngs-bioinformatics-summit-europe</guid>
  <pubDate>Sat, 13 Jul 2013 17:02:34 -0500</pubDate>
  <link></link>
  <title><![CDATA[NGS &amp; Bioinformatics Summit Europe]]></title>
  <description><![CDATA[
<p>NGS &amp; Bioinformatics Summit Europe </p>

<p>Conference </p>

<p>7th   to  8th October 2013 <br />Berlin, Germany </p>

<p>Website: https://www.gtcbio.com/conference/ngseurope-overview <br />Contact person: Kristen Starkey </p>

<p>We welcome you to join us at GTC’s NGS &amp; Bioinformatics Summit Europe on October 7-8, 2013 in Berlin, Germany. </p>

<p>Organized by: GTC <br />Deadline for abstracts/proposals: 7th September 2013</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/32374/ra-bioinformatics-at-jnu-new-delhi-india</guid>
  <pubDate>Thu, 27 Apr 2017 03:29:58 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at JNU, New Delhi, INDIA]]></title>
  <description><![CDATA[
<p>School of Computational &amp; Integrative Sciences<br />Jawaharlal Nehru University<br />New Delhi-110067, INDIA</p>

<p>Date: April 24th. 2017	Last Date: May 6th 2017<br />PROJECT ID: 632</p>

<p>The following posts are urgently required to be filled for the Department of Biotechnology, Government of India funded project jointly running with IIIT-Hyderabad &amp; JNU, entitled "Computational Core for Plant Metabolomics" administrated by Prof Indira Ghosh, School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110 067.<br />NB: For all the posts, preference will be given to candidates with a good knowledge of Python and/or R in UNIX platform , knowledge of JAVA will also get a special consideration.</p>

<p>1.	RA / Research Associate (Metabolic engineering/Computational Biologist)</p>

<p>Salary: Rs. 36000/- + HRA</p>

<p>Vacancy: 1</p>

<p>Essential Qualifications: PhD in Bioinformatics /Mathematics/Computer Science with experience in analyzing high throughput omics-based data/Analysis of Network Biology/Chemoinformatics/Computational Biology related Software development. Published paper in the field is a must to prove the experience. Special consideration will be given if have experience in Industry, teaching &amp; product development.</p>

<p>Desired Skills: Prior experience in handling and guiding bioinformatics, metabolomics data, planning of new research area in metabolic driven network , collaborating with industry , preparing and filing reports etc. Will be expected to communicate with user groups and coordinate with LIMS group in Hyderabad and the Cheminformatics group in Delhi.</p>

<p>2.	Project SRF (Network model building/Systems biology integration)</p>

<p>Salary*: Rs.18000/- + HRA</p>

<p>Vacancy: 1</p>

<p>Essential Qualifications: M.Tech in Computational Biology with project experience or Masters / B.Tech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Mathematical Model building using Computational Biology tools &amp; related Database / Network analysis etc. For M.Sc/B.Tech, Published paper in peer-reviewed Journal whereas for M.Tech, the degree obtained in computational biology is a must.</p>

<p>Desired Skills: Will be expected to manage ongoing research activities in LIMS, interact with LIMS group, build network model using data compiled by experimentalist, prepare and file reports and associated project work etc. Familiarity with plant systems biology and genomics /metabolite resources related to plant metabolomics is desirable.</p>

<p>More at http://www.jnu.ac.in/Career/currentjobs.htm</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/859/boku-chair-of-bioinformatics</guid>
  <pubDate>Sun, 14 Jul 2013 12:37:23 -0500</pubDate>
  <link></link>
  <title><![CDATA[Boku Chair of Bioinformatics]]></title>
  <description><![CDATA[
<p>The Bioinformatics group at Boku University has two main areas of interest, underpinning a common goal, the study of complex systems in living organisms. To overcome the engineered redundancies and combinatorial effects prevalent in higher eukaryotes, novel views augmenting the classical gene by gene approaches are required. We combine<br />Work to establish improved quantitative experimental assays (such as microarrays or differential in-gel electrophoresis) and<br />Development of modern computational methods (such as hierarchical probabilistic models or integration of heterogeneous data sources)</p>

<p>Link @ http://bioinf.boku.ac.at/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32399/mapping-ngs</guid>
	<pubDate>Tue, 02 May 2017 07:58:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32399/mapping-ngs</link>
	<title><![CDATA[Mapping NGS]]></title>
	<description><![CDATA[<p>NGS data are just a bunch of sequences, you have no idea which region in the genome each sequences comes from, which gene it represents...<br>To know that you have to align the sequences to the reference sequence. The reference sequence is in most cases the full genome sequence but sometimes, a library of EST sequences is used.<br>In either way, aligning your sequence reads to the reference sequence is called mapping.</p>
<p>The most used mappers of DNA-seq data are&nbsp;<a href="http://bio-bwa.sourceforge.net/" target="_blank">BWA</a>&nbsp;and&nbsp;<a href="http://bowtie-bio.sourceforge.net/bowtie2/index.shtml" target="_blank">Bowtie</a>&nbsp;for DNA-Seq data and&nbsp;<a href="http://tophat.cbcb.umd.edu/" target="_blank">Tophat</a>,&nbsp;<a href="https://github.com/alexdobin/STAR" target="_blank">STAR</a>&nbsp;or&nbsp;<a href="http://www.ccb.jhu.edu/software/hisat/index.shtml" target="_blank">HISAT</a>&nbsp;for RNA-Seq data. Mappers differ in which options they can take in, how fast and how accurate they are. Bowtie is faster than BWA, but looses some sensitivity (does not map an equal amount of reads to the correct position in the genome).</p><p>Address of the bookmark: <a href="http://wiki.bits.vib.be/index.php/Mapping_of_NGS_data" rel="nofollow">http://wiki.bits.vib.be/index.php/Mapping_of_NGS_data</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/870/6-phd-students-tu-dresden</guid>
  <pubDate>Sun, 14 Jul 2013 13:42:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[6 PhD Students @ TU Dresden]]></title>
  <description><![CDATA[
<p>At TU Dresden, Faculty of Computer Science, the DFG Research Training Group GRK 1907 “Role-based Software Infrastructures for continuous-context-sensitive Systems” offers the positions of 6 PhD Students (E 13 TV-L)</p>

<p>for applicants interested in performing high-quality research on the connection between software engineering, database systems, and theoretical computer science as well as their applications in bioinformatics and business informatics. The research programme will start on October 1, 2013 until 30.09.2016. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG).</p>

<p>This research programme is a joint activity of Professors Lehner, Assmann, Baader, Baier, Schill, Schlegel, Schroeder, and Strahringer at TU Dresden. Alongside their research, an individual mentoring and qualification approach are arranged with specialized courses that prepare them optimally for their research, a research seminar where they can meet internationally renowned researchers in the field, and soft skills and language courses.</p>

<p>Requirements: Applicants should have an excellent academic record, and hold a MSc (or an equivalent university degree) in computer science or related disciplines (such as mathematics, bioinformatics or business informatics). Fluency in spoken and written English is required. Applicants with a good knowledge of software engineering or one of the application areas mentioned above are preferred. TU Dresden is committed to increase the proportion of women in research.</p>

<p>Applications from women are particularly welcome. The same applies to disabled people.</p>

<p>Please send enquiries to: wolfgang.lehner@tu-dresden.de</p>

<p>Applications consist of a CV, the names of two referees, transcipts of documents summarizing their academic performance, and a statement of interest. Application by email in pdf format is preferred, and should be submitted to wolfgang.lehner@tu-dresden.de in an electronically signed and encrypted form by July 30, 2013 (stamped arrival date of the university central mail service applies). Alternatively, applications can be sent to: TU Dresden, Fakultät Informatik, Institut für Systemarchitektur, Prof.  Dr.-Ing.  Wolfgang Lehner, 01062 Dresden, Germany.</p>

<p>Shortlisted candidates will be invited to Dresden in the middle of August to give a presentation on their Master’s thesis and discuss their research interest with the participating professors. Candidates that have not yet finished their degree when they send in their application should send preliminary transcripts of their academic records as well as a letter by the thesis adviser that comments on their progress so far and on the expected date of completion of their MSc or equivalent degree.</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</guid>
	<pubDate>Fri, 05 May 2017 06:11:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</link>
	<title><![CDATA[Bacterial genome assembly !!]]></title>
	<description><![CDATA[<p>This tutorial will serve as an example of how to use free and open-source genome assembly and secondary scaffolding tools to generate high quality assemblies of&nbsp;bacterial sequence data. The bacterial sample used in this tutorial will be referred&nbsp;to simply&nbsp;as &ldquo;Species&rdquo; since it is&nbsp;live data. This data is paired-end data, meaning that there are forward and reverse reads, which we will designate as Sample_R1.fastq and Sample_R2.fastq, respectively.</p>
<p>https://github.com/jennomics/WorkflowPaper/blob/master/Genome%20Assembly%20and%20Annotation.md</p><p>Address of the bookmark: <a href="http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/" rel="nofollow">http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/864/the-laboratoire-de-genomique-fonctionelle</guid>
  <pubDate>Sun, 14 Jul 2013 13:03:18 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Laboratoire de genomique fonctionelle]]></title>
  <description><![CDATA[
<p>One persistent challenge of post genome biology remains the determination of the functions of all potential genes. In mammals this task is formidable given that a single gene can produce numerous protein isoforms through alternative pre-mRNA splicing. Protein isoforms from a single gene can have diverse, and in some cases antagonistic, functions. AS plays a pivotal biological role in protein diversity and developmental regulation. It is now believed that AS occurs in up to 74% of human genes, making it more of a rule than an exception.</p>

<p>Link @ http://lgfus.ca/public/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32631/barrnap-bacterial-ribosomal-rna-predictor</guid>
	<pubDate>Fri, 12 May 2017 09:24:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32631/barrnap-bacterial-ribosomal-rna-predictor</link>
	<title><![CDATA[Barrnap: Bacterial ribosomal RNA predictor]]></title>
	<description><![CDATA[<p>Barrnap predicts the location of ribosomal RNA genes in genomes. It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S), mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S).</p>
<p>It takes FASTA DNA sequence as input, and write GFF3 as output. It uses the new NHMMER tool that comes with HMMER 3.1 for HMM searching in RNA:DNA style. NHMMER binaries for 64-bit Linux and Mac OS X are included and will be auto-detected. Multithreading is supported and one can expect roughly linear speed-ups with more CPUs.&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/tseemann/barrnap" rel="nofollow">https://github.com/tseemann/barrnap</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/872/jayaram-lab</guid>
  <pubDate>Sun, 14 Jul 2013 14:04:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[Jayaram Lab]]></title>
  <description><![CDATA[
<p>Responsible (a) for developing Chemgenome, Bhageerath &amp; Sanjeevini methods &amp; softwares for genome annotation, protein tertiary structure prediction &amp; computer aided drug design respectively, (b) for setting up a multi-teraflop supercomputing facility for Bioinformatics &amp; Computational Biology at IIT Delhi, and (c) for making the hardware and software freely accessible at (www.scfbio-iitd.res.in) to the global scientific user community.</p>

<p>Faculty facilitator/Founder Director for two start-up companies (Leadinvent incubated at IIT, Delhi from 2006-2009 &amp; Novoinformatics, under incubation at IIT Delhi since 2011).</p>

<p>Research Interest <br />Genome Analysis, Protein Structure Prediction and Drug Design.</p>

<p>Link @ http://www.scfbio-iitd.res.in/</p>
]]></description>
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