<?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/26925?offset=450</link>
	<atom:link href="https://bioinformaticsonline.com/related/26925?offset=450" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25301/jrf-bioinformatics-at-cuk</guid>
  <pubDate>Sat, 28 Nov 2015 03:26:21 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics at CUK]]></title>
  <description><![CDATA[
<p>JRF job opportunity in Central University of Kerala (CUK) on temporary basis </p>

<p>Project Title : "Targeting TAL effector mediated susceptibility for durable and broad-spectrum resistance to bacterial blight in Rice"</p>

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

<p>Qualification : MSc in any subject under Life Science or Bioinformatics/ B.Tech in Bioinformatics + 1 yr experience </p>

<p>Stipend : Rs. 14,000/-</p>

<p>How to apply</p>

<p>Interested candidates are requested to send their applications explaining their interest in the position with an updated CV to Dr. Ginny Antony, Assistant Professor, Department of Plant Science, School of Biological Sciences, Central University of Kerala, Padannakkad, Kasaragod, Kerala - 671 314 email: ginnycuk2013@gmail.com on or before 20th December, 2015.</p>

<p>More at http://cukerala.ac.in/index.php?option=com_content&amp;view=article&amp;id=1022:applications-invited-for-the-post-of-jrf-department-of-plant-science&amp;catid=106&amp;Itemid=593&amp;lang=en</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25503/assistant-professor-computational-biology-and-bioinformatics-in-navi-mumbai</guid>
  <pubDate>Fri, 04 Dec 2015 20:40:59 -0600</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor - Computational Biology and Bioinformatics in Navi Mumbai]]></title>
  <description><![CDATA[
<p>No. ACTREC / ADVT-A/2/2015 <br />Pay in Pay band and Grade Pay : PB-3 (Rs 15,600-39,100) Pay in pay band Rs 21,900+ G.P. of Rs 7,600 <br />Total emoluments = 82,000/- p.m. &amp; nbsp <br />Educational Qualification : Ph.D. or MD/Ph.D. <br />Experience : Post MD / Ph.D. Research experience of 5 years The last date of application submission is January 15th, 2016. <br />Interested candidates shall send the applications through email: office.sao(at)actrec.gov.in. <br />For More Details : www.actrec.gov.in/data%20files/Vacancies/2015/Faculty-Positions-SOE-24-11-15.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25410/srfjrf-bioinformatics-at-ciari</guid>
  <pubDate>Fri, 04 Dec 2015 00:10:09 -0600</pubDate>
  <link></link>
  <title><![CDATA[SRF/JRF Bioinformatics at CIARI]]></title>
  <description><![CDATA[
<p>Realizing the importance of Island Agriculture to meet the requirements of local population and tourists, Indian Council of Agricultural research (ICAR) established Central Island Agricultural Research Institute, Port Blair on June 23rd, 1978 by merging different regional research stations of ICAR institutes located in Islands. The ultimate aim of CIARI is the developments of island agricultural production technologies which utilizes the strengths of the island and convert the constraints in opportunities, without causing any ill effect to the fragile ecosystem of the island.The institute has made tremendous progress in the Agriculture development of the islands during the last three decades. Keeping in view the natural resources of the islands diversity, fragile ecosystem, research program would be designed to maximize the productivity without disturbing to the islands ecosystem to provide better and decent livelihood and as a source of revenue and resource generation. Research and development in Agriculture sector should cover all disciplines in order to have a balanced progress in all disciplines for the overall benefits of the farmers of these islands.</p>

<p>Position I</p>

<p>Job Title : Junior Research Fellow</p>

<p>No. of Posts : One</p>

<p>Project : Establishment of sub distributed information centre</p>

<p>Qualification : M.Sc in Basic Science with NET or B.Sc in professional course with NET or M.Sc in professional course</p>

<p>Desired Experience : Experience in Bioinformatics and molecular biology</p>

<p>Payscale : Rs. 25000 per month</p>

<p>Age Limit : Upto 35 for men and 40 for women with 5 years relaxation to SC/ST and 3 years relaxation for OBC.</p>

<p>Position II</p>

<p>Job Title : Traineeship</p>

<p>No. of Posts : One</p>

<p>Project : Establishment of sub distributed information centre</p>

<p>Qualification : B.Sc Bioinformatics /Biotechnology / Life Science / Computer Science</p>

<p>Desired Experience : Experience in Bioinformatics and molecular biology</p>

<p>Payscale : Rs. 8000 per month</p>

<p>Age Limit : Upto 35 for men and 40 for women with 5 years relaxation to SC/ST and 3 years relaxation for OBC.</p>

<p>Position III</p>

<p>Job Title : Studentship</p>

<p>No. of Posts : Two</p>

<p>Project : Establishment of sub distributed information centre</p>

<p>Qualification : B.Sc Bioinformatics /Biotechnology / Life Science / Computer Science</p>

<p>Desired Experience : Experience in Bioinformatics and molecular biology</p>

<p>Payscale : Rs. 8000 per month</p>

<p>Age Limit : Upto 35 for men and 40 for women with 5 years relaxation to SC/ST and 3 years relaxation for OBC.</p>

<p>How to Apply : Candidates who meet the requirements can attend the walk in interview at CIARI,Port Blair on 09.12.2015 10.30AM.</p>

<p>http://icar-ciari.res.in/employment/9-12-15.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25674/post-doc-position-at-labgem-evry-france</guid>
  <pubDate>Fri, 11 Dec 2015 06:24:00 -0600</pubDate>
  <link></link>
  <title><![CDATA[Post-doc position at LABGeM - Evry, France]]></title>
  <description><![CDATA[
<p>The LABGeM team (CEA/Genoscope, CNRS UMR 8030, France, Dir. Claudine Médigue) is developing integrated approaches which combines bioinformatics methods based (i) on genomic and metabolic contexts, (ii) on an orignal metabolic network representation and (iii) on a structural classification of active sites for the discovery of new metabolic enzymatic activities.</p>

<p>We are hiring a post-doctoral fellow for the development of innovative bioinformatics methods to explore metabolic networks and enzyme families. These methods will be based on protein family analysis and graph approaches combining genomic and metabolic contexts.</p>

<p>For more details, please see this link : http://goo.gl/tHQOqk</p>

<p>Qualifications:<br />PhD degree in bioinformatics or computational biology<br />- Previous experience in network or protein family analysis<br />- Programming skills (C/C++, Python, Java) and in common biostatistical analyses<br />- Team player, innovative and creative thinking, good oral and written communication skills</p>

<p>24 months, Post Doctoral position<br />Start: from March 2016<br />Place: CEA, Genoscope UMR8030, LABGeM (Laboratory of Bioinformatics Analyses for Genomics and Metabolism), Evry, France<br />Contact: David Vallenet, vallenet@genoscope.cns.fr<br />Publications: https://scholar.google.com/citations?user=rJNPLSAAAAAJ<br />Remuneration per month: from 2,850 €</p>

<p>Interested candidates should send their CV, statement of research interests, and contact information of at least 2 references to David Vallenet (vallenet@genoscope.cns.fr).</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26221/project-assistant-at-iiser-mohali</guid>
  <pubDate>Fri, 29 Jan 2016 11:04:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[Project Assistant at IISER Mohali]]></title>
  <description><![CDATA[
<p>Project Assistant Job position in Indian Institute of Science Education &amp; Research (IISER) Mohali </p>

<p>Title : In silico understanding of molecular basis of recognition, binding, and regulation of mRNA by STAR family of transcriptional regulators.</p>

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

<p>Department : Science and Technology</p>

<p>Qualifications : M.Sc./B.Tech in computational life sciences, computational chemistry, computational natural sciences or allied areas. Working experience in MD simulations, bioinformatics, molecular modeling, and drug designing is desirable and plus</p>

<p>Emoluments : As per DST norms<br />How to apply</p>

<p>Applicants are requested to send application along with bio-data and a summary of previous projects (if any) as a PDF file with the e-mail to Dr. Monika Sharma, Email: mnsharma@iisermohali.ac.in. Last date of applications is 17:00 IST. Feb 15, 2016. Shortlisted candidates will be called for interview on Feb 22, 2016. </p>

<p>More at http://14.139.227.202/tenders/tenderinvite/index.php/iiserm-project-openings/554-applications-are-invited-to-work-as-project-assistant-in-a-dst-inspire-research-project-funded-by-department-of-science-and-technology-india</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26453/stacks</guid>
	<pubDate>Wed, 24 Feb 2016 15:52:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26453/stacks</link>
	<title><![CDATA[Stacks]]></title>
	<description><![CDATA[<p>Stacks is a software pipeline for building loci from short-read sequences, such as those generated on the Illumina platform. Stacks was developed to work with restriction enzyme-based data, such as RAD-seq, for the purpose of building genetic maps and conducting population genomics and phylogeography.</p>
<p>More at http://catchenlab.life.illinois.edu/stacks/</p><p>Address of the bookmark: <a href="http://catchenlab.life.illinois.edu/stacks/" rel="nofollow">http://catchenlab.life.illinois.edu/stacks/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</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/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</guid>
	<pubDate>Sat, 21 May 2016 22:42:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</link>
	<title><![CDATA[Bpipe - a tool for running and managing bioinformatics pipelines]]></title>
	<description><![CDATA[<p>Bpipe provides a platform for running big bioinformatics jobs that consist of a series of processing stages - known as 'pipelines'.</p>
<ul>
<li>January 20th, 2016 - New! Bpipe 0.9.9 released!</li>
<li>Download <a href="http://download.bpipe.org/versions/bpipe-0.9.9.tar.gz">latest</a>, <a href="http://download.bpipe.org">all</a></li>
<li><a href="http://docs.bpipe.org">Documentation</a></li>
<li><a href="https://groups.google.com/forum/#%21forum/bpipe-discuss">Mailing List</a> (Google Group)</li>
</ul>
<p>Bpipe has been published in <a href="http://bioinformatics.oxfordjournals.org/content/early/2012/04/11/bioinformatics.bts167.abstract">Bioinformatics</a>! If you use Bpipe, please cite:</p>
<p><em>Sadedin S, Pope B &amp; Oshlack A, Bpipe: A Tool for Running and Managing Bioinformatics Pipelines, Bioinformatics</em></p><p>Address of the bookmark: <a href="http://docs.bpipe.org/" rel="nofollow">http://docs.bpipe.org/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/38886/evaluation-of-genome-assembly-software-based-on-long-reads</guid>
	<pubDate>Fri, 01 Feb 2019 11:55:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/38886/evaluation-of-genome-assembly-software-based-on-long-reads</link>
	<title><![CDATA[Evaluation of genome assembly software based on long reads]]></title>
	<description><![CDATA[<p>TGS technologies have been used to produce highly accurate de novo assemblies of hundreds of microbial genomes and highly contiguous reconstructions of many dozens of plant and animal genomes, enabling new insights into evolution and sequence diversity. They have also been applied to resequencing analyses, to create detailed maps of structural variations in many species. Also, these new technologies have been used to fill in many of the gaps in the human reference genome.</p><p>In this report, we compare and evaluate several genome assembly software based on TSG technology. The experimentation has been performed on 4 reference genomes and the results evaluated with the QUAST software. The 11 software that have been evaluated are: Celera Assembler , Falcon , Miniasm, Newbler , SGA Assembler, Smartdenovo, Abruijn, Ra, DBG2OLC, Spades and Cerulean. The first 8 software use only long reads, while the 3 last software can merge long and short reads</p>]]></description>
	<dc:creator>BioStar</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/38886" length="382699" type="application/pdf" />
</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>

</channel>
</rss>