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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/10741?offset=250</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25149/project-assistant-ii-job-vacancies-in-national-institute-of-oceanography-nio-goa</guid>
  <pubDate>Fri, 06 Nov 2015 01:33:22 -0600</pubDate>
  <link></link>
  <title><![CDATA[Project Assistant-II job vacancies in National Institute of Oceanography (NIO Goa)]]></title>
  <description><![CDATA[
<p>Vacancy no : GAP0423/1509-15</p>

<p>Project Assistant-II job vacancies in National Institute of Oceanography (NIO Goa)</p>

<p>Project Title and Code : Biotechnology Information System. -- GAP0423</p>

<p>Qualification : M.Sc Bioinformatics / Zoology / Botany / Environmental Science. Desirable : Basic understanding of biodiversity concept is desirable</p>

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

<p>Age : 28 Years</p>

<p>Place of Posting : Goa</p>

<p>Consolidated Stipend Per Month : Rs.16000/-</p>

<p>Job Requirement : Collection and handling of biodiversity data as assigned by the scientists and working with in-house biodiversity data management applications and software<br />How to apply</p>

<p>Candidates satisfying requirements may attend the Walk-in-interview on 12.11.2015, 10.00 AM at NIO Dona Paula, Goa-403004 along with their bio-data, attested copies of certificates &amp; mark lists in proof of qualification (SSC onwards), age, experience and testimonials. Candidates should bring a photo identity proof at the time of registration</p>

<p>More at http://www.nio.org/index/option/com_vacgoa/task/show/title/Goa/tid/6/sid/28/thid/64</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25293/srfjrf-bioinformatics-at-national-bureau-of-animal-genetic-resources</guid>
  <pubDate>Thu, 26 Nov 2015 01:54:07 -0600</pubDate>
  <link></link>
  <title><![CDATA[SRF/JRF Bioinformatics at National Bureau of Animal Genetic Resources]]></title>
  <description><![CDATA[
<p>National Bureau of Animal Genetic Resources </p>

<p>SRF Job vacancies in National Bureau of Animal Genetic Resources (NBAGR) on contractual basis</p>

<p>No. of Posts : 03</p>

<p>Qualifications : Master degree in any one of discipline/ Subjects Biotechnology/Bioinformatics/Life Sciences/ Computer Applications with 4 years/5 years of Bachelor’s degree. Candidates having post graduate degree in above mentioned subjects with 3 years Bachelor’s degree should be NET qualified.</p>

<p>Note : i. The Ph.D. Degree holders are eligible for the posts. ii. The Master’s degree holders with the integrated degrees like B.Tech. &amp; M. Tech. (5 years) are eligible. iii. Graduates with three years Bachelor’s degree, who have acquired professional Master’s degree (3 years) like M.Sc. (Ag.), Masters in Computer Applications, M. Tech., etc., are eligible.</p>

<p>Desirable : The candidates should have zeal to work in R environment and NGS data analysis</p>

<p>Emolument : Rs. 28,000/- </p>

<p>Age Limit : 35 year for Men and 40 years for Women in case of SRF on the date of Interview.<br />How to apply</p>

<p>Walk-in-Interview is proposed to be held at National Bureau of Animal Genetic Resources, Karnal (Haryana)-132 001 at 10:30 AM on 02.12.2015. Interested candidates may attend Walk-in-Interview at 10:30 AM on 02.12.2015 alongwith original certificates and typed bio-data with one set of attested copies of each their certificates with passport size photograph.</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25303/ciab-recruits-scientist-engineer-informatics-officer</guid>
  <pubDate>Sat, 28 Nov 2015 03:40:28 -0600</pubDate>
  <link></link>
  <title><![CDATA[CIAB Recruits Scientist, Engineer, Informatics Officer]]></title>
  <description><![CDATA[
<p>Center of Innovative and Applied Bioprocessing (CIAB) - Punjab</p>

<p>Center of Innovative and Applied Bioprocessing (CIAB) invites applications to recruit on vacant posts of Scientist, Associate Plant Manager/ Plant Engineer, Informatics Officer. Applications against these Government Jobs can be submitted on or before 7th January 2016.<br />CIAB Vacancy 2015 Details</p>

<p>9. Research &amp; Development – Informatics Officer<br />Qualification: M. Tech or M.E. in computer science or information technology or bioinformatics with 4 years of R&amp;D experience (after Master’s Degree) in an R&amp;D organization with work profile of large data assembly, analysis.<br />Age Limit: 45 years<br />How to Apply : Duly filled-in applications in prescribed application format along with copies of required documents should be reach to: Chief Exec</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25406/assistant-professor-bioinformatics-at-alagappa-university</guid>
  <pubDate>Thu, 03 Dec 2015 23:30:43 -0600</pubDate>
  <link></link>
  <title><![CDATA[ASSISTANT PROFESSOR Bioinformatics at ALAGAPPA UNIVERSITY]]></title>
  <description><![CDATA[
<p>ALAGAPPA UNIVERSITY<br /> Recruitment and Sarkari Naukri for the Post of ASSISTANT PROFESSOR Bioinformatics<br />Job Description UGC scale of pay is applicable. For eligibility qualifications and other norms, please refer to the ?Instructions to the Candidates? available with the application forms which can be had on payment of Rs.520/- inclusive of Rs.20/- for postage. For SC/ST, Rs.320/- inclusive of Rs.20/- for postage on enclosure of a copy of the community certificate. Payment is to be made by means of Demand Draft drawn on any nationalized bank in favour of ?The Registrar, Alagappa University? payable at Karaikudi. Candidates can also download the application form and instructions to the candidates from httpwww.alagappauniversity.ac Filled-in application should reach on or before 19.10.2015<br />Salary for Job : Rs.15600-39100+AGP Rs.6000<br />Education : Good academic record with at least 55 marks (or an equivalent grade in a point scale wherever grading system is followed) at the Masters Degree level in a relevant subject from an Indian University, or an equivalent degree from an accredited foreign university. Besides fulfilling the above qualifications, the candidate must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/SET.Notwithstanding anything contained in sub-clauses (i) and (ii) above, the candidates, who are, or have been awarded a Ph.D. degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulations 2009, shall be exempted from the requirement of the minimum eligibility condition of NET/SLET/SET for recruitment and appointment of Assistant Professor or equivalent positions in Universities/Colleges/Institutions.<br />Number of Vacancies : 02<br />Naukri Location : Other City(s) in Tamil Nadu<br />Address : KARAIKUDI ? 630 003<br />Last Date to Apply : 2015-12-04<br />Apply Process : written test/interview</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/26927/phylographer-graph-visualization-tool</guid>
	<pubDate>Wed, 06 Apr 2016 19:06:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26927/phylographer-graph-visualization-tool</link>
	<title><![CDATA[PhyloGrapher - Graph Visualization Tool]]></title>
	<description><![CDATA[<p><strong>PhyloGrapher</strong><span>&nbsp;is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).</span><strong>PhyloGrapher</strong><span>&nbsp;is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;to visualize any type of relations between elements.&nbsp;</span></p>
<p><span>More at&nbsp;http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</span></p><p>Address of the bookmark: <a href="http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html" rel="nofollow">http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</guid>
	<pubDate>Tue, 26 Apr 2016 12:18:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</link>
	<title><![CDATA[Smash: An alignment-free method to find and visualise rearrangements between pairs of DNA sequences]]></title>
	<description><![CDATA[<p><strong>Smash is a completely alignment-free method/tool to find and visualise genomic rearrangements</strong><span>. The detection is based on&nbsp;</span><strong>conditional exclusive compression</strong><span>, namely using a FCM (Markov model), of high context order (typically 20). For visualisation, Smash outputs a&nbsp;</span><strong>SVG image</strong><span>, with an&nbsp;</span><strong>ideogram</strong><span>output architecture, where the patterns are represented with several&nbsp;</span><strong>HSV values</strong><span>&nbsp;(only value varies). The method can perform both in small- and large-scale. Nevertheless is more directed to large-scale since that the main aim of the research is to&nbsp;</span><strong>know where the large-scale [chromosomal by chromosome] of several primates was equal/different, having at a glance a map of the entire genomes</strong><span>.</span></p><p>Address of the bookmark: <a href="http://bioinformatics.ua.pt/software/smash/" rel="nofollow">http://bioinformatics.ua.pt/software/smash/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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