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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/12944?offset=200</link>
	<atom:link href="https://bioinformaticsonline.com/related/12944?offset=200" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25094/project-assistant-bioinformatics</guid>
  <pubDate>Mon, 02 Nov 2015 03:23:09 -0600</pubDate>
  <link></link>
  <title><![CDATA[Project Assistant BioInformatics]]></title>
  <description><![CDATA[
<p>Project Assistant BioInformatics</p>

<p>Eligibility : ME/M.Tech(Bio-Informatics/Bio-Chemistry Engg), MSc(Bio-Informatics), BE/B.Tech</p>

<p>Location : Pune</p>

<p>Last Date : 16 Nov 2015</p>

<p>Hiring Process : Face to Face Interview</p>

<p>No. Bio/NCIM/3 </p>

<p>Project Assistant II Jobs opportunity in National Chemical Laboratory (NCL) on temporary basis</p>

<p>Project Code No. : GAP312626</p>

<p>Title of the Project : Microbial ecology and distribution of geochemical cycling genes in an hot spring ecosystem</p>

<p>No. of Post : 01</p>

<p>Qualifications : M.Sc./B.Tech/M.Tech in Computational biology/ Bioinformatics from recognized university with minimum 60 % marks (aggregate) </p>

<p>Desirable : Good knowledge of computational skills, Linux (command line and GUI) and Unix; Perl / Python / R /C-programming. Practical knowledge of analysis of Next generation sequence datasets (amplicon sequencing, whole metagenome, and complete genome sequencing) with reference to microbes. Analysis and statistical validation of NGS data generated from different chemistry platforms. Some wet-lab experience in microbial system would be an added advantage as project involves some travel.</p>

<p>Emoluments : Rs. 16,000/- </p>

<p>Age Limit : 28 years</p>

<p>The application with the above information duly signed together with photo-copies of relevant certificates/testimonials should be addressed to : The Head, NCIM Resource Centre (Attn Dr. M.S. DHARNE), National Chemical Laboratory, Pune 411 008, so as to reach on or before 16th November 2015.</p>

<p>More at http://www.ncl-india.org/files/JoinUs/JobVacancies/TemporaryJobs.aspx?menuid=ql6&amp;childmenustripid=divSubQL6</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25147/pre-or-postdoctoral-research-fellowship-in-structural-bioinformatics-at-padova</guid>
  <pubDate>Thu, 05 Nov 2015 22:15:12 -0600</pubDate>
  <link></link>
  <title><![CDATA[Pre- or postdoctoral research fellowship in Structural Bioinformatics at Padova]]></title>
  <description><![CDATA[
<p>A research fellowship for a software developer is available at the BioComputing UP Laboratory, University of Padova (URL: http://protein.bio.unipd.it/).<br />A highly motivated and creative candidate is sought to work on structural bioinformatics. Specifically, the project entails the development of novel methods, tools and databases for the analysis of protein structures.</p>

<p>The BioComputing UP Laboratory, headed by Prof. Silvio Tosatto, is a dynamic group of a dozen people working on several aspects of prediction of protein structure &amp; function employing techniques at the intersection between biology, medicine, chemistry, physics &amp; computer science.<br />Our aim is to integrate the development of novel methods and their application to biologically relevant problems.</p>

<p>We are looking for candidates with a solid Bioinformatics background, programming experience (Python, C++ and/or Java) and good knowledge of molecular biology (protein structure/function). Good knowledge of statistics as well as experience in using database systems (MongoDB, MySQL and/or Postgres) is desirable. Candidates should have a degree with top marks, optionally hold a PhD, and be highly motivated to work on interdisciplinary research. Good knowledge of English, an open-minded spirit, being collaborative and creative are crucial.</p>

<p>The fellowship, which should start as soon as possible, is renewable and initially for one year. It will be commensurate to experience, can be extended depending on performance and may lead to a PhD degree. The successful candidate will be working full-time at the BioComputing UP Laboratory, University of Padova. Travel support for conferences and/or research visits abroad is provided.<br />To apply, please send your CV, with a motivation letter and brief description of your research background as well as the names of two (or more) references to: biocomp@bio.unipd.it. </p>

<p>Start date: As soon as possible</p>

<p>Duration: 1 year, renewable</p>

<p>Salary on grant: Commesurate to experience</p>

<p>Contact Person (Referent): Silvio Tosatto</p>

<p>Ref. E-Mail: biocomp@bio.unipd.it</p>

<p>Tel: +39 049 827 6269<br />Fax: +39 049 827 6260</p>

<p>Group Web Page: http://protein.bio.unipd.it/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25308/traineeship-at-biomedical-informatics-centre-pgimer-chandigarh</guid>
  <pubDate>Sun, 29 Nov 2015 03:04:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[Traineeship at Biomedical Informatics Centre  PGIMER  Chandigarh]]></title>
  <description><![CDATA[
<p>Biomedical Informatics Centre</p>

<p>PGIMER</p>

<p>Chandigarh</p>

<p>invites application for a project dissertation program for students who have completed their first year of M.Sc. in Bioinformatics.</p>

<p>This is an exciting opportunity for Master's students to train in modern methods in Bioinformatics. The duration of the training will be four to six months, starting from January 2016.</p>

<p>Education: Pursuing M.Sc. Bioinformatics</p>

<p>Essential: Post graduate applicants should have completed their first year and should be in the third semester or first half of the second year.</p>

<p>Only students who are willing to spend a minimum period of 4 months to a maximum of six months, without any break, would be eligible for the program.</p>

<p>How to Apply: Candidates interested in the above project dissertation program should apply online. Send your CV, Scanned copy of letter of recommendation from Head of Institution along with Registration form in the given format should be sent to: info@bicpgi.org</p>

<p>Please mention clearly “Project dissertation &amp; your Name” in the Subject.</p>

<p>The last date for application is December 23, 2015</p>

<p>Note: Selected candidates may please note that the program is free of cost and would not provide any financial aid for transport and stay. Name of the selected candidates would be posted on the centre website by December 31, 2015.</p>

<p>Incomplete applications will be rejected.</p>

<p>For more information visit our website: http://bic-pgi.org/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25302/ra-bioinformatics-at-jamia-hamdard</guid>
  <pubDate>Sat, 28 Nov 2015 03:37:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at Jamia Hamdard]]></title>
  <description><![CDATA[
<p>Research Associate, Bioinformatics Facility<br />Jamia Hamdard - New Delhi, Delhi<br />Research Associate, Bioinformatics Facility, Jamia Hamdard.<br />Emoluments: Rs. 22,000 + HRA 30%<br />Qualification: PhD or equivalent or having 3 years of research, teaching and design and development experience after M. Pharm./M.VSc./M.E./M.Tech. PhD in life sciences and related areas with experience in Bioinformatics may apply. Company Info.<br />Jamia Hamdard</p>

<p>Jamia Hamdard New Delhi - 110062 Additional Information States &amp; U.T State &amp; Union Territories Delhi How To Apply Apply Details<br />Last date of application: December 5, 2015 Web/Notification URL http://www.jamiahamdard.ac.in/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26569/genome-stability-laboratory</guid>
  <pubDate>Mon, 07 Mar 2016 04:16:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[Genome Stability Laboratory]]></title>
  <description><![CDATA[
<p>The bakers yeast, Saccharomyces cerevisiae is an ideal model organism to understand mechanisms of meiotic chromosome segregation. In S. cerevisiae and in mammals, the majority of meiotic crossovers are formed through a highly conserved MSH4p-MSH5p, MLH1p-MLH3p dependent pathway. We are interested in charactering the role of these complexes in crossover formation and distribution among all homolog pairs. Errors in this process are linked to congenital birth defects in humans such as Down's syndrome.Our laboratory is also interested in understanding the effect of genetic background on mutation rate variation using S. cerevisiae as a model. These studies are relevant for understanding cancer progression, genome evolution and architecture. We use high- throughput genomic methods as well as classical genetics to achieve these aims. </p>

<p>More at http://faculty.iisertvm.ac.in/~nishantkt/index.html</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25504/uas-dharwad-assistant-professor</guid>
  <pubDate>Fri, 04 Dec 2015 21:06:23 -0600</pubDate>
  <link></link>
  <title><![CDATA[UAS Dharwad Assistant Professor]]></title>
  <description><![CDATA[
<p>UNIVERSITY OF AGRICULTURAL SCIENCES, DHARWAD</p>

<p>Applications are invited in the prescribed form for filling up the following posts of Teachers and Service Personnel from the candidates who are qualified as on the last date fixed for receipt of applications in the University of Agricultural Sciences, Dharwad.</p>

<p>I. ASSISTANT PROFESSOR CADRE (Scale of pay Rs.15600-39100 + AGP Rs. 6000) (UGC / ICAR pay-scales)</p>

<p>I. Re-notified posts:</p>

<p>9. Assistant Professor of Bioinformatics 1 GM-1</p>

<p>More Info : https://sites.google.com/a/uasd.in/recruitment/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</guid>
	<pubDate>Mon, 29 Feb 2016 17:39:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</link>
	<title><![CDATA[scikit-learn]]></title>
	<description><![CDATA[<p>Machine Learning in Python</p>
<p>Simple and efficient tools for data mining and data analysis<br> Accessible to everybody, and reusable in various contexts<br> Built on NumPy, SciPy, and matplotlib<br> Open source, commercially usable - BSD license</p>
<p>More at&nbsp;http://scikit-learn.org/stable/index.html</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://scikit-learn.org/stable/auto_examples/index.html" rel="nofollow">http://scikit-learn.org/stable/auto_examples/index.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26752/rna-seq-de-novo-assembly-using-trinity</guid>
	<pubDate>Wed, 23 Mar 2016 05:53:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26752/rna-seq-de-novo-assembly-using-trinity</link>
	<title><![CDATA[RNA-Seq De novo Assembly Using Trinity]]></title>
	<description><![CDATA[<p>Trinity, developed at the <a href="http://www.broadinstitute.org">Broad Institute</a> and the <a href="http://www.cs.huji.ac.il">Hebrew University of Jerusalem</a>, represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data. Trinity combines three independent software modules: Inchworm, Chrysalis, and Butterfly, applied sequentially to process large volumes of RNA-seq reads. Trinity partitions the sequence data into many individual de Bruijn graphs, each representing the transcriptional complexity at at a given gene or locus, and then processes each graph independently to extract full-length splicing isoforms and to tease apart transcripts derived from paralogous genes. Briefly, the process works like so:</p>
<ul>
<li>
<p><em>Inchworm</em> assembles the RNA-seq data into the unique sequences of transcripts, often generating full-length transcripts for a dominant isoform, but then reports just the unique portions of alternatively spliced transcripts.</p>
</li>
<li>
<p><em>Chrysalis</em> clusters the Inchworm contigs into clusters and constructs complete de Bruijn graphs for each cluster. Each cluster represents the full transcriptonal complexity for a given gene (or sets of genes that share sequences in common). Chrysalis then partitions the full read set among these disjoint graphs.</p>
</li>
<li>
<p><em>Butterfly</em> then processes the individual graphs in parallel, tracing the paths that reads and pairs of reads take within the graph, ultimately reporting full-length transcripts for alternatively spliced isoforms, and teasing apart transcripts that corresponds to paralogous genes.</p>
</li>
</ul>
<p>More at https://github.com/trinityrnaseq/trinityrnaseq/wiki</p>
<p>......................................................................................................................................</p>
<p>Download Trinity <a href="https://github.com/trinityrnaseq/trinityrnaseq/releases">here</a>.</p>
<p>Build Trinity by typing 'make' in the base installation directory.</p>
<p>Assemble RNA-Seq data like so:</p>
<pre><code> Trinity --seqType fq --left reads_1.fq --right reads_2.fq --CPU 6 --max_memory 20G 
</code></pre>
<p>Find assembled transcripts as: 'trinity_out_dir/Trinity.fasta'</p><p>Address of the bookmark: <a href="https://github.com/trinityrnaseq/trinityrnaseq/wiki" rel="nofollow">https://github.com/trinityrnaseq/trinityrnaseq/wiki</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26999/discovar</guid>
	<pubDate>Mon, 18 Apr 2016 11:59:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26999/discovar</link>
	<title><![CDATA[DISCOVAR]]></title>
	<description><![CDATA[<p><strong>DISCOVAR</strong> is a new variant caller and <strong>DISCOVAR <em>de novo</em></strong> a new genome assembler, both designed for state-of-the-art data. Their inputs are chosen to optimize quality while keeping costs low. Currently it takes as input Illumina reads of length 250 or longer &mdash; produced on MiSeq or HiSeq 2500 &mdash; and from a single PCR-free library. These data enable a level of completeness and continuity that was not previously possible.</p>
<p><strong>DISCOVAR</strong> can call variants on a region by region basis, potentially tiling an entire large genome. DISCOVAR variant calling is under active development and transitioning to VCF.</p>
<p><strong>DISCOVAR <em>de novo</em></strong> can generate <em>de novo</em> assemblies for both large and small genomes. It currently does not call variants.</p>
<p>More at https://www.broadinstitute.org/software/discovar/blog/?page_id=14</p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/software/discovar/blog/" rel="nofollow">https://www.broadinstitute.org/software/discovar/blog/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27078/homer-software-for-motif-discovery-and-next-gen-sequencing-analysis</guid>
	<pubDate>Tue, 26 Apr 2016 03:48:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27078/homer-software-for-motif-discovery-and-next-gen-sequencing-analysis</link>
	<title><![CDATA[HOMER:  Software for motif discovery and next-gen sequencing analysis]]></title>
	<description><![CDATA[<p><span>This tutorial covers topics independently of HOMER, and represents knowledge which is important to know before diving head first into more advanced analysis tools such as HOMER.</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/computerSetup.html">Setting up your computing environment</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/retrieveFiles.html">Retrieving and storing sequencing files</a>&nbsp;(your own data or from public sources)</li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/fastqFiles.html">Checking sequence quality, trimming, general sequence manipulation</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/mapping.html">Mapping reads to a reference genome</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/samfiles.html">Manipulating SAM/BAM alignment files</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/genomeBrowsers.html">Visualizing data in a genome browser</a></li>
</ol>
<p><br>RNA-Seq</p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/rnaseqCufflinks.html">De novo transcript discovery and differential analysis with Cufflinks</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/rnaseqR.html">Differential expression analysis with R/Bioconductor</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/clustering.html">Clustering of large expression datasets (microarray or RNA-Seq)</a></li>
</ol>
<p><br><span>Microarray</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/affymetrix.html">Basic analysis of Affymetrix Gene Expression Arrays using R/Bioconductor</a></li>
</ol>
<p><span>General Tips for Data Analysis</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/excelTips.html">Excel workarounds, adding gene annotation, X-Y plots tips, etc.</a></li>
</ol><p>Address of the bookmark: <a href="http://homer.salk.edu/homer/basicTutorial/" rel="nofollow">http://homer.salk.edu/homer/basicTutorial/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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