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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37905?offset=400</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/18741/a-powerful-yet-simple-gene-set-analysis-tool-for-interpreting-rna-seq-and-ngs-results</guid>
	<pubDate>Thu, 30 Oct 2014 09:19:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/18741/a-powerful-yet-simple-gene-set-analysis-tool-for-interpreting-rna-seq-and-ngs-results</link>
	<title><![CDATA[A powerful, yet simple, gene set analysis tool for interpreting RNA-seq and NGS results.]]></title>
	<description><![CDATA[<p>LifeMap Sciences is introducing&nbsp;<a href="http://geneanalytics.genecards.org/">GeneAnalytics</a>, our new gene set analysis tool, which is applicable for NGS results and differentially expressed gene lists from variable sources. GeneAnalytics provides&nbsp;gene associations with tissues &amp; cells, diseases, pathways, GO terms and compounds.</p><p>Our main advantages over other similar tools are:</p><ul>
<li>GeneAnalytics is very simple and intuitive to use.</li>
<li>GeneAnalytics is based on our proprietary databases &ndash;&nbsp;<strong>GeneCards</strong>, MalaCards, PathCards and LifeMap Discovery, each of them integrates information from a very large number of resources.</li>
<li>GeneAnalytics supplies links for extensive background information on each of the matched results.</li>
</ul><p>&nbsp;</p><p>I invite you to try it out for free at&nbsp;geneanalytics.genecards.org, and would be happy to hear your comments and thoughts on how we can improve.</p><p>&nbsp;</p><p>Yours,</p><p>Shani Ben-Ari Fuchs</p><p>LifeMap Sciences Team</p>]]></description>
	<dc:creator>Shani</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</guid>
	<pubDate>Wed, 11 Feb 2015 04:59:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</link>
	<title><![CDATA[Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer']]></title>
	<description><![CDATA[<div><p><strong>Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer'</strong></p><p><strong>Abstract</strong></p><p>Whole exome DNA sequencing (WES) or whole genome DNA sequencing (WGS) allows detection of mutations and polymorphisms in all exonic and genomic regions, respectively, while messenger RNA sequencing (RNA-Seq) enables quantitative analysis of gene expression. Mutations in the genome result in diverse transcriptional aberrations that can be missed in a stand-alone WES/WGS analysis. An integration of DNA variant analysis and RNA-Seq analysis enables one to investigate the consequences of genomic changes in the RNA transcripts including germline and somatic changes, imprinting, RNA editing and allele specific expression (ASE). In this webinar, we will demonstrate this integrated approach using Strand NGS to identify high confidence mutations, RNA editing events and ASE in cancer.</p><p><strong>Webinar Details</strong></p><table width="100%" border="1" cellspacing="0" cellpadding="0">
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<p style="text-align: center;"><br /> <strong>Sessions</strong></p>
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<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>San Francisco Time<br /> (PST)</strong></a></p>
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<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Tokyo Time<br /> (GMT+09:00)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Berlin Time<br /> (GMT+01:00)</strong></a></p>
</td>
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<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Mumbai Time<br /> (GMT+05:30)</strong></a></p>
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</tr>
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<td>
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 1</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 12:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 5:30 PM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 2:00 PM</p>
</td>
</tr>
<tr>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 2</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:00 AM</p>
</td>
<td>
<p style="text-align: center;">26 Feb<br /> 2:00 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 6:00 PM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 10:30 PM</p>
</td>
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</tbody>
</table><p><strong style="font-size: 12.8000001907349px;">Register here: </strong><a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p><p><strong>About Speaker:</strong></p><p>Dr. Veena Hedatale, has a PhD in Plant Genetics from The Radboud University, Netherlands focused on meiosis and recombination. Her prior academic experience at Cornell University was on genetic mapping and gene transformation in Rice. She has worked with Monsanto, and contributed to data mining, database development as well as gene/promoter/pathway discovery for traits related to yield and stress in crop species. At Strand, Veena has worked on Pharmacogenomic analysis of targets and Gene family analysis projects. Currently, she is part of the Strand NGS Application Science team and is involved in the analysis of next generation sequencing data.</p><p>Please feel free to contact us 24/5, for availing free online training or if you have any questions.</p></div><div><p><strong style="font-size: 12.8000001907349px;">Email:</strong> sales@strandngs.com</p><p><strong>Phone (USA):</strong> 1-800-752-9122</p><p><strong>Phone (ROW):</strong> +1-650-353-5060</p><p>&nbsp;</p></div>]]></description>
	<dc:creator>Yeshodari</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23174/scaffolding-of-a-bacterial-genome-using-minion-nanopore-sequencing</guid>
	<pubDate>Tue, 07 Jul 2015 16:59:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23174/scaffolding-of-a-bacterial-genome-using-minion-nanopore-sequencing</link>
	<title><![CDATA[Scaffolding of a bacterial genome using MinION nanopore sequencing]]></title>
	<description><![CDATA[<p><span>Second generation sequencing has revolutionized genomic studies. However, most genomes contain repeated DNA elements that are longer than the read lengths achievable with typical sequencers, so the genomic order of several generated contigs cannot be easily resolved. A new generation of sequencers offering substantially longer reads is emerging, notably the Pacific Biosciences (PacBio) RS II system and the MinION system, released in early 2014 by Oxford Nanopore Technologies through an early access program.</span></p><p>Address of the bookmark: <a href="http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html" rel="nofollow">http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24297/bioinformatics-walkin-at-nii</guid>
  <pubDate>Fri, 04 Sep 2015 21:48:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics WalkIn at NII]]></title>
  <description><![CDATA[
<p>ADVERTISEMENT OF WALK-IN-INTERVIEW</p>

<p>NAME OF THE POST : Bioinformatician (Part time 3 days in a week) (One Position only)</p>

<p>DURATION : One Year</p>

<p>NAME OF THE PROJECT : Next generation sequencing facility</p>

<p>EDUCATIONAL QUALIFICATIONS : At least a Masters degree in Bioinformatics and Bachelors degree in any stream of life sciences</p>

<p>REQUIREMENTS :</p>

<p>Around 5 years of experience and proven track record in next generation sequence data analysis (supported by publications in peer-reviewed journals), ability to analyze transcriptomics, Chip-seq, and small RNA –seq data.</p>

<p>: Should have the ability to analyze raw primary data generated by Illumina next generation sequencing platforms and create / troubleshoot custom analysis Pipelines.</p>

<p>Should have ability to handle all downstream secondary and tertiary data analysis using commercially available as well as open source softwares (transcriptomics, ChIP-seq, small RNA-seq)</p>

<p>Apart from these, the applicant should have knowledge of the following: Programming: Perl and Python. Operating system:</p>

<p>Linux and Windows. NGS Analysis tools: Maq, BWA, Bowtie, SAM tools, BEDTools, MACS, Galaxy, FastQC, Bismark, MEDIPS, Tophat, Cufflinks, AvadisNGS, CLC Genomics Workbench, Galaxy, BaseSpace, Trinity Statistics: Microsoft Excel and R. Database: MySQL Genome Browser: UCSC, Ensemble, IGV, IGB Motif Analysis Tools: MEME Suite, Transfac and RSAT Functional Annotation Tools: DAVID, GeneCodis, Gene Cards Networking Tools: Cytoscape</p>

<p>EMOLUMENTS : The incumbent will be paid a fee of Rs. 2000/- per sitting/ per day.</p>

<p>SCIENTIST NAME : Dr. Arnab Mukhopadhyay,</p>

<p>Staff Scientific V Next generation sequencing facility</p>

<p>SCIENTIST’S E-MAIL ID : arnab@nii.ac.in</p>

<p>WALK IN INTERVIEW ON : 18th September, 2015</p>

<p>REGISTRATION OF CANDIDATES: 10.30 AM to 11.00 AM</p>

<p>PLEASE NOTE- 1. CANDIDATE MAY FILL UP APPLICATION IN THE PRECRIBED FORMAT ALONG WITH NECESSARY DOCUMENTS FOR VERIFICATION. 2. APPLICATIONS CONTAINING INCOMPLETE INFORMATION SHALL NOT BE ENTERTAINED. 3. DATE OF PASSING THE EXAMINATIONS MUST BE INDICATED CLEARLY. 4. ONLY REGISTERED CANDIDATES WILL BE INTERVIEWED. 5. NO TA/DA WILL BE PAID FOR ATTENDING THE INTERVIEW PRESCRIBED FORM 1. NAME 2. FATHER’S NAME 3. MOTHER’S NAME 4. DATE OF BIRTH 5. SEX (MALE/FEMALE) 6. CATEGORY (SC/ ST/ OBC/ PH) 7. ADDRESS a. (CORRSPONDENCE) b. (PERMANENT) 8. E MAIL, TELEPHONE NO. &amp; MOBILE No (if any) 9. ACADEMIC &amp; PROFESSIONAL QUALIFICATIONS NAME OF EXAMINATION PASSED WITH SUBJECTS YEAR OF PASSING BOARD/ UNIVERSITY PERCENTAGE/ DIVISION REMARKS 10. PAST EXPERIENCE &amp; PRESENT EMPLOYMENT, IF ANY 11. CANDIDATES SHOULD STATE CLEARLY WHETHER THEY HAVE BEEN AWARDED PH.D DEGREE OR THESIS HAS BEEN SUBMITTED. 12. HAVE YOU APPLIED FOR A POSITION EARLIER IN THE INSTITUTE? IF SO:- (1) THE DETAILS OF THE PROJECT AND PROJECT INVESTIGATOR (2) IF CALLED FOR INVERVIEW, RESULTS THEREOF</p>

<p>More at http://www1.nii.res.in/sites/default/files/walkininterview-18sept2015.pdf</p>
]]></description>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26968/scalce</guid>
	<pubDate>Fri, 15 Apr 2016 05:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26968/scalce</link>
	<title><![CDATA[SCALCE]]></title>
	<description><![CDATA[<p><span>SCALCE (</span><code>/skeɪlz/</code><span>, a.k.a. boosting&nbsp;</span><span style="text-decoration: underline;">S</span><span>equence&nbsp;</span><span style="text-decoration: underline;">C</span><span>ompression&nbsp;</span><span style="text-decoration: underline;">A</span><span>lgorithms using&nbsp;</span><span style="text-decoration: underline;">L</span><span>ocally&nbsp;</span><span style="text-decoration: underline;">C</span><span>onsistent</span><span style="text-decoration: underline;">E</span><span>ncoding) is a tool for compressing FASTQ files. It is designed specifically for the Illumina-generated FASTQ files, but supports any valid FASTQ with consistent read lengths.&nbsp;</span></p>
<p><span>More at&nbsp;http://sfu-compbio.github.io/scalce/</span></p><p>Address of the bookmark: <a href="http://sfu-compbio.github.io/scalce/" rel="nofollow">http://sfu-compbio.github.io/scalce/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27080/mrfast-micro-read-fast-alignment-search-tool</guid>
	<pubDate>Tue, 26 Apr 2016 03:50:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27080/mrfast-micro-read-fast-alignment-search-tool</link>
	<title><![CDATA[mrFAST:  Micro Read Fast Alignment Search Tool]]></title>
	<description><![CDATA[<p><span>mrFAST is a read mapper that is designed to map short reads to reference genome with a special emphasis on the discovery of structural variation and segmental duplications. mrFAST maps short reads with respect to user defined error threshold, including indels up to 4+4 bp. This manual, describes how to choose the parameters and tune mrFAST with respect to the library settings. mrFAST is designed to find&nbsp;</span><strong><span style="text-decoration: underline;">'all'</span></strong><span>&nbsp; mappings for a given set of reads, however it can return one "best" map location if the relevant parameter is invoked.</span></p>
<p><span>More at&nbsp;http://mrfast.sourceforge.net/manual.html</span></p><p>Address of the bookmark: <a href="http://mrfast.sourceforge.net/manual.html" rel="nofollow">http://mrfast.sourceforge.net/manual.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27323/cutadapt</guid>
	<pubDate>Fri, 13 May 2016 04:54:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27323/cutadapt</link>
	<title><![CDATA[cutadapt]]></title>
	<description><![CDATA[<p>Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.</p>
<p>Cleaning your data in this way is often required: Reads from small-RNA sequencing contain the 3&rsquo; sequencing adapter because the read is longer than the molecule that is sequenced. Amplicon reads start with a primer sequence. Poly-A tails are useful for pulling out RNA from your sample, but often you don&rsquo;t want them to be in your reads.</p>
<p>Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.</p>
<p>Cutadapt comes with an extensive suite of automated tests and is available under the terms of the MIT license.</p>
<p>If you use cutadapt, please cite <a href="http://dx.doi.org/10.14806/ej.17.1.200">DOI:10.14806/ej.17.1.200</a> .</p><p>Address of the bookmark: <a href="https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart" rel="nofollow">https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27440/stampy</guid>
	<pubDate>Fri, 20 May 2016 19:13:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27440/stampy</link>
	<title><![CDATA[Stampy]]></title>
	<description><![CDATA[<p><strong>Stampy&nbsp;</strong><span>is a package for the mapping of short reads from illumina sequencing machines onto a reference genome. It's recommended for most workflows, including those for genomic resequencing, RNA-Seq and Chip-seq. Stampy excels in the mapping of reads containing that contain sequence variation relative to the reference, in particular for those containing insertions or deletions.</span></p><p>Address of the bookmark: <a href="http://www.well.ox.ac.uk/project-stampy" rel="nofollow">http://www.well.ox.ac.uk/project-stampy</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27847/anvio</guid>
	<pubDate>Thu, 16 Jun 2016 18:15:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27847/anvio</link>
	<title><![CDATA[Anvio]]></title>
	<description><![CDATA[<p>In a nutshell</p>
<p>Anvi&rsquo;o is an analysis and visualization platform for &lsquo;omics data.</p>
<p>Please find the methods paper here: https://peerj.com/articles/1319/</p>
<p>Anvi&rsquo;o would not have been possible without the help of many people who directly or indirectly contributed to its development. Here is the acknowledgements section of our methods paper</p>
<p><span>An analysis and visualization platform for 'omics data</span><span>&nbsp;</span><span><a href="http://merenlab.org/projects/anvio">http://merenlab.org/projects/anvio</a></span></p>
<p><span>Paper&nbsp;https://peerj.com/articles/1839/</span></p><p>Address of the bookmark: <a href="https://github.com/meren/anvio" rel="nofollow">https://github.com/meren/anvio</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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