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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31302?offset=1460</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37233/rna-seq-analysis-workshop-course-materials</guid>
	<pubDate>Tue, 03 Jul 2018 08:14:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37233/rna-seq-analysis-workshop-course-materials</link>
	<title><![CDATA[RNA-seq Analysis Workshop Course Materials]]></title>
	<description><![CDATA[RNAseq can be roughly divided into two "types":

Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves our ability to reconstruct transcripts. This category would obviously include humans and most model organisms but excludes the majority of truly biologically intereting species (e.g., Hyacinth macaw);

Reference genome-free - no genome assembly for the species of interest is available. In this case one would need to assemble the reads into transcripts using de novo approaches. This type of RNAseq is as much of an art as well as science because assembly is heavily parameter-dependent and difficult to do well.
In this lesson we will focus on the Reference genome-based type of RNA seq.

http://chagall.med.cornell.edu/RNASEQcourse/<p>Address of the bookmark: <a href="http://chagall.med.cornell.edu/RNASEQcourse/" rel="nofollow">http://chagall.med.cornell.edu/RNASEQcourse/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28818/senior-manager-bioinformatics-operations-at-rgcb-india</guid>
  <pubDate>Wed, 17 Aug 2016 03:19:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Manager (Bioinformatics Operations) at RGCB, India]]></title>
  <description><![CDATA[
<p>No. RGCB/ADVT/ADMN&amp;TECH/01/2016</p>

<p>August 17, 2016</p>

<p>RGCB invites applications for the following positions from Indian citizens with prescribed qualifications. Full details including job description, additional desirable qualifications, etc. are described below.</p>

<p>Code No. 1</p>

<p>Senior Manager (Bioinformatics Operations)</p>

<p>(To download application format, click here )</p>

<p>Scale of Pay</p>

<p>PB-3 Rs.15600-39100 + Grade Pay Rs.6600/-</p>

<p>Number of Positions</p>

<p>1 (General)</p>

<p>Minimum Qualifications</p>

<p>PhD in Bioinformatics, Biotechnology, Life Sciences or Computer Science applied to biological questions.<br />A minimum of 5 years documented experience in national or state government R&amp;D centers or state and central universities.<br />Track record of research funding and peer reviewed publications.<br />Proficiency using statistical analysis software or libraries such as R or Matlab.<br />Experience with a general scripting language such as Python, Ruby, or Pearl<br />Experience working with Next Generation Sequencing data<br />Proficiency with data visualization tools (Spotfire, Tableau, R, Python, etc.)<br />Experience with an object-oriented language such as Java, C++ or C# and familiarity with standard software development best practices: source code control, unit testing, in-code documentation and automated build environments.<br />Excellent listening, time management, organizational and interpersonal skills<br />Excellent communication skills, including the ability to illustrate problems and generate solutions<br />Management skills – demonstrated through the successful management of a team or large projects.<br />Broad and deep knowledge of computational methods for high-throughput sequence analysis and interpretation.<br />Extensive experience in delivering bioinformatics as a service and conducting training programs.<br />Experience of working with a production, customer-focused environment and business development projects.<br />Experience with management of funding and financial sustainability.<br />Demonstrated ability to work in a team environment and ability to lead and motivate an effective team, and also work as a good team player.<br />Good problem solver, able to logically identify solutions to technical problems.<br />Able to see the bigger picture and contribute towards strategic direction of Platforms and Pipelines teams.<br />Responsibilities</p>

<p>This position will involve cross-functional teamwork to build and develop bioinformatics tools and provide analysis for ongoing clinical trials.<br />Collaborate with biomarker scientists, clinical investigators and pipeline teams to build analytical tools.<br />Implement and evaluate new algorithms for R&amp;D.<br />Support Research and Development teams by analyzing NGS data to identify predictive response markers<br />Lead training programs in Computational Biology and Bioinformatics.</p>

<p>More at http://rgcb.res.in/positions.php</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server</guid>
	<pubDate>Fri, 07 Dec 2018 08:04:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server</link>
	<title><![CDATA[GWASpro: A High-Performance Genome-Wide Association Analysis Server]]></title>
	<description><![CDATA[<p>GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model (LMM). GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10,000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://bioinfo.noble.org/GWASPRO/" rel="nofollow">https://bioinfo.noble.org/GWASPRO/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28819/research-project-at-iit-madras</guid>
  <pubDate>Wed, 17 Aug 2016 03:26:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Project at IIT, Madras]]></title>
  <description><![CDATA[
<p>Two project positions are available to work on (i) molecular modeling and molecular dynamics simulations and (ii) development of bioinformatics databases and tools at Protein Bioinformatics Lab, Department of Biotechnology, IIT Madras.</p>

<p>Duration : Initially for a period of one year. Extendable based on the performance.</p>

<p>Qualification: (i) MSc in Bioinformatics, Biotechnology, Physics, Biophysics, Biochemistry,Computer Science with NET (UGC/CSIR/GATE/BINC/INSPIRE etc) qualification. (OR) (ii) M. Tech in Bioinformatics, Biotechnology</p>

<p>Additional qualification: Programming skills</p>

<p>Candidates who fulfill the requirements of IIT have the possibility to register for PhD.</p>

<p>Fellowship: Rs.25,000 and HRA.</p>

<p>Applicants are encouraged to send the CV to the coordinator by postal mail and e-mail. The deadline to receive the applications is 31st August 2016. The project coordinator has the discretion to restrict the number of candidates to be called for interview to a reasonable limit on the basis of qualifications and experience higher than the minimum prescribed in the announcement.</p>

<p>Project Co-ordinator:</p>

<p>Dr. M. Michael Gromiha <br />Department of Biotechnology <br />Indian Institute of Technology Madras <br />Chennai 600036 <br />Email: gromiha@iitm.ac.in</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28829/jrf-bioinformatics-at-manit-india</guid>
  <pubDate>Thu, 18 Aug 2016 02:48:53 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics at MANIT, India]]></title>
  <description><![CDATA[
<p>Advt. No.: Maths./577/2016 Date: 12/08/2016<br />JRF Bioinformatics Job Position in Maulana Azad National Institute of Technology (MANIT) purely temporary basis<br />Project Title : “Computational Approach to Study Complex Biological Network of Diseases using Molecular Data”<br />Essential Qualifications &amp; experience: M.Tech in Bioinformatics/ Computational System biology/Computer Science or M.Sc. in Bio informatics/Biotechnology/Mathematics/Statistics from recognized University/ Institute. Preference will be given to GATE/NET qualified candidates.<br />No. of Post : 01<br />Fellowship: INR 12000<br /> <br />How to apply<br />The duly completed application on prescribed format along with copies of supporting documents must reach to: office of the Dr. Usha Chouhan, Principal Investigator, Department of Mathematics, Bioinformatics &amp; Computer Applications, Maulana Azad National Institute of Technology, Bhopal-462003 on or before 31/08/2016. A soft copy of the application should also be sent to ycchouhan@gmail.com  email address of Principal Investigator.</p>

<p>More at http://www.web.manit.ac.in/Year%202016/JRF/walk%20in.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44539/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</guid>
	<pubDate>Wed, 15 May 2024 14:36:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44539/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</link>
	<title><![CDATA[Bactopia: a Flexible Pipeline for Complete Analysis of Bacterial Genomes]]></title>
	<description><![CDATA[<p dir="auto">Bactopia is a flexible pipeline for complete analysis of bacterial genomes. The goal of Bactopia is to process your data with a broad set of tools, so that you can get to the fun part of analyses quicker!</p>
<p dir="auto">Bactopia can be split into two main parts:&nbsp;<a href="https://bactopia.github.io/latest/beginners-guide/">Bactopia Analysis Pipeline</a>, and&nbsp;<a href="https://bactopia.github.io/latest/bactopia-tools/">Bactopia Tools</a>.</p>
<p dir="auto">Bactopia Analysis Pipeline is the main&nbsp;<em>per-isolate</em>&nbsp;workflow in Bactopia. Built with&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>, input FASTQs (local or available from SRA/ENA) are put through numerous analyses including: quality control, assembly, annotation, minmer sketch queries, sequence typing, and more.</p>
<p dir="auto"><a href="https://github.com/bactopia/bactopia/blob/master/data/bactopia-workflow.png" target="_blank"><img src="https://github.com/bactopia/bactopia/raw/master/data/bactopia-workflow.png" alt="Bactopia Overview" style="border: 0px;"></a></p>
<p dir="auto">Bactopia Tools are a set a independent workflows fo</p><p>Address of the bookmark: <a href="https://github.com/bactopia/bactopia" rel="nofollow">https://github.com/bactopia/bactopia</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28926/scientist-at-advanced-centre-for-treatment-research-and-education-in-cancer-navi-mumbai-maharashtra</guid>
  <pubDate>Tue, 30 Aug 2016 04:16:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Scientist at Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra]]></title>
  <description><![CDATA[
<p>Scientist <br />Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra<br />Scientist (One position) <br />Project: Bioinformatics centre DBT- Sub-DIC at ACTREC <br />Funding agency: DBT Grant No.232 </p>

<p>Duration of the Project: Six Months from the date of appointment can be extended further for six months <br />Essential Qualification and Experience: 1st Class Masters Degree in Bioinformatics or Life Sciences equivalent degree from a recognized University with 4 years R&amp;D experience in Bioinformatics or relevant subjects from recognized institutes. <br />OR <br />Ph.D. degree in Bioinformatics or Life Sciences from recognized University. <br />M.Sc. degree obtained after a one year course will not be considered. <br />Experience: Research/teaching experience in Bioinformatics or relevant subjects form recognized Institute(s). </p>

<p>More at http://www.actrec.gov.in/data%20files/Vacancies/2016/AV-scin-stud-trainee-6-Sept-16.docx</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29262/bioinformatics-jobs-at-chittaranjan-national-cancer-institute</guid>
  <pubDate>Thu, 29 Sep 2016 09:36:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics jobs at Chittaranjan National Cancer Institute]]></title>
  <description><![CDATA[
<p>Chittaranjan National Cancer Institute Advertisement No.497/2016 Invites Applications For Senior Scientific Officer, Gr. II </p>

<p>Note: Experience in the following field required: Molecular cancer cytogenetic and genetic toxicology Molecular drug Designing and targeted therapy Cancer genomics, proteomics, bioinformatics and next generation sequencing Therapeutic stem cell research and gene therapy Molecular cancer immunology and immunotherapy Molecular epidemiology Tumor endocrinology Translation research Ultra structural/tissue engg/development biology research Virus and cancer Molecular pathology No. of Posts: 11 (Eleven), (SC-1, OBC-3, UR-7) </p>

<p>Location: Kolkata (Calcutta) Salary: Rs.15600-39100 + Grade, Pay Rs.5400/- </p>

<p>For details kindly refer to the Employment News dated 24-30 September, 2016 and in the Institute’s Website: http://www.cnci.org.in </p>

<p>Last date for receipt of applications is 30 days from the date of notification in the Employment News. Director Chittaranjan National Cancer Institute 378, S.P. </p>

<p>Institute’s Website: http://www.cnci.org.in</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33912/mesquite-a-modular-system-for-evolutionary-analysis</guid>
	<pubDate>Tue, 18 Jul 2017 07:42:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33912/mesquite-a-modular-system-for-evolutionary-analysis</link>
	<title><![CDATA[Mesquite: A modular system for evolutionary analysis]]></title>
	<description><![CDATA[<p><span>Mesquite is modular, extendible software for evolutionary biology, designed to help biologists organize and analyze comparative data about organisms. Its emphasis is on phylogenetic analysis, but some of its modules concern population genetics, while others do non-phylogenetic multivariate analysis. Because it is modular, the analyses available depend on the modules installed.</span></p>
<p><span>http://mesquiteproject.wikispaces.com/</span></p><p>Address of the bookmark: <a href="https://github.com/MesquiteProject/MesquiteCore/releases" rel="nofollow">https://github.com/MesquiteProject/MesquiteCore/releases</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34465/rnaseq-data-analysis-links</guid>
	<pubDate>Mon, 27 Nov 2017 16:28:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34465/rnaseq-data-analysis-links</link>
	<title><![CDATA[RNAseq data analysis links !]]></title>
	<description><![CDATA[<p>RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping.</p><p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4728800/" target="_blank">A survey of best practices for RNA-seq data analysis</a></p><p><a href="http://www.bioconductor.org/help/workflows/rnaseqGene/" target="_blank">RNA-seq workflow: gene-level exploratory analysis and DE</a></p><p><a href="https://github.com/crazyhottommy/RNA-seq-analysis" target="_blank">RNAseq analysis notes from Tommy Tang</a></p><p><a href="http://web.stanford.edu/group/wonglab/doc/RNA-seq-talk-JSM2010.pdf" target="_blank">Analysis of RNA ‐ Seq Data</a></p><p><a href="https://f1000research.com/articles/5-1408/v2" target="_blank">RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR</a></p><p><a href="http://www.nature.com/nprot/journal/v7/n3/full/nprot.2012.016.html" target="_blank">Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.</a></p><p><a href="https://www.ebi.ac.uk/training/online/course/ebi-next-generation-sequencing-practical-course/rna-sequencing/rna-seq-analysis-transcriptome" target="_blank">EBI RNA-Seq exercise</a></p><p><a href="https://f1000research.com/articles/5-1574/v1" target="_blank">An open RNA-Seq data analysis pipeline tutorial with an example</a></p><p><a href="https://ycl6.gitbooks.io/rna-seq-data-analysis/rna-seq_analysis_workflow.html" target="_blank">RNA-Seq Analysis Workflow</a></p><p><a href="http://www.nature.com/nprot/journal/v11/n9/full/nprot.2016.095.html" target="_blank">Transcript-level expression analysis of RNA-seq experiments</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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