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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44707?offset=540</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4946/crcri-bioinfomatics-walk-in-on-08102013</guid>
  <pubDate>Fri, 27 Sep 2013 10:59:53 -0500</pubDate>
  <link></link>
  <title><![CDATA[CRCRI Bioinfomatics Walk In on 08.10.2013]]></title>
  <description><![CDATA[
<p>Walk-in-Interview for recruitment of one Project Fellow for a period of 10 months purely on temporary basis is proposed to be held at Central Tuber Crops Research Institute, Sreekariyam, Thiruvananthapuram for a KSCSTE funded project entitled “PARTICIPATORY DEVELOPMENT OF A WEB BASED USER FRIENDLY CASSAVA EXPERT SYSTEM”</p>

<p>Salary: Rs. 10,000/- per month.</p>

<p>Age limit: 35 for men and 40 for women &amp; SC/ST.</p>

<p>Qualification: First class in M. Sc (Agriculture)/MCA/M.Sc (IT)/ M. Sc (Computer Application)/M.Sc (Bioinformatics)/M.Sc (Geoinformatics).</p>

<p>Desirable: Two years experience in web design and web programming.</p>

<p>Date &amp; time of interview: 08.10.2013, 10 am</p>

<p>Interested candidates may appear for an interview at this institute along with their application in plain paper containing the following particulars viz. (1) Name (2) Father/Husband/Guardian’s Name (3) date of birth &amp; age as on 01.10.2013 (4) Permanent address (5) Address for communication (6) Email address and Telephone No. with code (7) Qualification (8) National fellowship like ICAR/CSIR/UGC etc. if any (9) Whether SC/ST/OBC (10) Details of experience (Attested copies of degree certificate, proof of age, mark sheets). Original certificates should be produced for verification.</p>

<p>No TA/DA will be admissible to the candidates attending the test. The selected candidate will have to join immediately.</p>

<p>Advertisement: http://www.ctcri.org/careers/mithra_SRF.doc</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36510/scallop-reference-based-transcriptome-assembler-for-rna-seq</guid>
	<pubDate>Tue, 08 May 2018 04:23:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36510/scallop-reference-based-transcriptome-assembler-for-rna-seq</link>
	<title><![CDATA[Scallop: reference-based transcriptome assembler for RNA-seq]]></title>
	<description><![CDATA[<p>Scallop is an accurate reference-based transcript assembler. Scallop features its high accuracy in assembling multi-exon transcripts as well as lowly expressed transcripts. Scallop achieves this improvement through a novel algorithm that can be proved preserving all phasing paths from reads and paired-end reads, while also achieves both transcripts parsimony and coverage deviation minimization.</p>
<p>Scallop paper has been published at&nbsp;<a href="https://www.nature.com/articles/nbt.4020"><span>Nature Biotechnology</span></a>. The datasets and scripts used in this paper to compare the performance of Scallop and other assemblers are available at&nbsp;<a href="https://github.com/Kingsford-Group/scalloptest"><span>scalloptest</span></a>.</p>
<p>Please also checkout the&nbsp;<span>podcast</span>&nbsp;about Scallop (thanks&nbsp;<a href="https://ro-che.info/">Roman Cheplyaka</a>&nbsp;for the interview). It is available at both&nbsp;<a href="https://bioinformatics.chat/scallop">the bioinformatics chat</a>&nbsp;and&nbsp;<a href="https://itunes.apple.com/us/podcast/the-bioinformatics-chat/id1227281398">iTunes</a>.</p>
<p>&nbsp;</p>
<p>https://github.com/Kingsford-Group/scallop</p><p>Address of the bookmark: <a href="https://github.com/Kingsford-Group/scallop" rel="nofollow">https://github.com/Kingsford-Group/scallop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5187/bioinformatics-algorithms-part-1-with-pavel-pevzner-phillip-e-c-compeau</guid>
	<pubDate>Mon, 30 Sep 2013 11:34:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5187/bioinformatics-algorithms-part-1-with-pavel-pevzner-phillip-e-c-compeau</link>
	<title><![CDATA[Bioinformatics Algorithms (Part 1)  with Pavel  Pevzner, Phillip E. C. Compeau,]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/t5t_nfzdzEg" frameborder="0" allowfullscreen></iframe><p>The course Bioinformatics Algorithms (Part 1) by Pavel Pevzner, Phillip E. C. Compeau, and Nikolay Vyahhi from University of California, San Diego will be offered free of charge to everyone on the Coursera platform. Sign up at http://www.coursera.org/course/bioinformatics.</p>]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43025/modular-efficient-and-constant-memory-single-cell-rna-seq-preprocessing</guid>
	<pubDate>Mon, 05 Apr 2021 11:19:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43025/modular-efficient-and-constant-memory-single-cell-rna-seq-preprocessing</link>
	<title><![CDATA[Modular, efficient and constant-memory single-cell RNA-seq preprocessing]]></title>
	<description><![CDATA[<p>With&nbsp;<strong>kallisto | bustools</strong>&nbsp;you can</p>
<ul>
<li>Generate a&nbsp;<em>cell x gene</em>&nbsp;or&nbsp;<em>cell x transcript equivalence class</em>&nbsp;count matrix</li>
<li>Perform RNA velocity and single-nuclei RNA-seq analsis</li>
<li>Quantify data from numerous technologies such as 10x, inDrops, and Dropseq.</li>
<li>Customize workflows for new technologies and protocols.</li>
<li>Process feature barcoding data such as CITE-seq, REAP-seq, MULTI-seq, Clicktags, and Perturb-seq.</li>
<li>Obtain QC reports from single-cell RNA-seq data</li>
</ul>
<p>The&nbsp;<strong>kallisto | bustools</strong>&nbsp;workflow is described in:</p>
<p>P&aacute;ll Melsted*, A. Sina Booeshaghi*, Lauren Liu, Fan Gao, Lambda Lu, Kyung Hoi (Joseph) Min, Eduardo da Veiga Beltrame, Kristj&aacute;n Eldj&aacute;rn Hj&ouml;rleifsson, Jase Gehring &amp; Lior Pachter&dagger;&nbsp;<a href="https://doi.org/10.1038/s41587-021-00870-2" target="_blank">Modular and efficient pre-processing of single-cell RNA-seq</a>, Nature Biotechnology (2021).</p>
<p>&nbsp;</p>
<p><span>Documentation and tutorials for the kallisto bustools workflow are available at&nbsp;</span><a href="http://pachterlab.github.io/kallistobustools">http://pachterlab.github.io/kallistobustools</a><span>.&nbsp;</span></p>
<p>https://www.nature.com/articles/s41587-021-00870-2</p><p>Address of the bookmark: <a href="https://pachterlab.github.io/kallistobustools/" rel="nofollow">https://pachterlab.github.io/kallistobustools/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5255/walk-in-interview-indian-agricultural-statistics-research-institute</guid>
  <pubDate>Wed, 02 Oct 2013 15:40:17 -0500</pubDate>
  <link></link>
  <title><![CDATA[Walk-in-Interview @ Indian Agricultural Statistics Research Institute]]></title>
  <description><![CDATA[
<p>Indian Agricultural Statistics Research Institute<br />Library Avenue, Pusa, New Delhi – 110012</p>

<p>Walk-in-Interview</p>

<p>Walk-in-interview will be held on October 5, 2013 at 10:00 A.M. at IASRI, New Delhi for a project “A New Distributed Computing Framework for Data Mining” funded by Department of Electronics and Information Technology, Government of India for the following posts. The appointment will be on contractual basis upto 14th October, 2015 or till the termination of the project whichever is earlier and the incumbent shall not have any claim for regular appointment under ICAR.</p>

<p>Research Associate</p>

<p>    Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or</p>

<p>    Post-Graduation in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 1st Division and at least two years of research experience</p>

<p>     Knowledge of Statistical Analysis /Bioinformatics tools for computational genomics.</p>

<p>     Knowledge of R/Perl programming language</p>

<p>Research Associate</p>

<p>    Ph.D. in Computer Science/ Computer Application / Bioinformatics/ Agricultural<br />    Statistics/ Statistics or equivalent or</p>

<p>    Post-Graduation in Computer Science/ Computer Application /Bioinformatics/ Agricultural Statistics/ Statistics or equivalent with 1st Division and at least two years of research experience</p>

<p>     Expertise in Java programming.<br />     Knowledge of system administration and networking under Linux environment.<br />     Knowledge of parallel programming and cluster computing.</p>

<p>Emoluments for Research Associate: Consolidated Rs:24000/- per month + HRA (for Ph.D. Degree holders) and Rs:23000/- per month + HRA (for Master’s Degree holders)</p>

<p>Age Limit: Age should be not more than 40 years (5 years relaxation for  SC/ST/women candidates and 3 years for OBC candidates as on date of interview).</p>

<p>Interested candidates are requested to appear for Walk-in-Interview on the date and time as specified above in Room No. 106, Training Cum Administrative Block of the Institute along with their application giving bio-data with attested copies of certificates, degrees, testimonials, etc. and one passport size photograph.</p>

<p>Original certificates/ Degrees are needed to be produced at the time of interview.</p>

<p>No T.A. /D.A. will be paid for appearing in the interview.</p>

<p>Advertisement: http://www.iasri.res.in/employment/employment.htm</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/10966/genxpro-gmbh</guid>
	<pubDate>Thu, 22 May 2014 07:18:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/10966/genxpro-gmbh</link>
	<title><![CDATA[GenXPro GmbH]]></title>
	<description><![CDATA[<p><strong>GenXPro</strong>&nbsp;GMbH is service provider for entire spectrum of nucleotide-based information&nbsp;of any biological sample. By combining intelligent data reduction techniques and&nbsp;latest next generation sequencing technologies, our service portfolio provides most accurate and cost efficient solutions for&nbsp;transcriptomic-, genomic- or epigenomic research.</p><p><span><span><strong><span>GENXPRO GMBH</span>,&nbsp;</strong></span></span><span>ALTENH&Ouml;FERALLEE 3,&nbsp;</span><span>60438 FRANKFURT MAIN,&nbsp;</span><span>GERMANY</span></p><p><span><span><strong>Website</strong></span>:&nbsp;<a href="http://www.genxpro.info/products_and_services/"></a><a href="http://www.genxpro.info/products_and_services/">http://www.genxpro.info/products_and_services/</a></span></p><p><span><strong>PHONE</strong>: +49 (0)69- 95 73 97 10,&nbsp;FAX: +49 (0)69- 95 73 97 06</span></p><p><span>EMAIL: info@genxpro.de</span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5422/shendure-lab</guid>
  <pubDate>Wed, 09 Oct 2013 14:21:58 -0500</pubDate>
  <link></link>
  <title><![CDATA[Shendure Lab]]></title>
  <description><![CDATA[
<p>The Shendure Lab is part of the Department of Genome Sciences at the University of Washington (Seattle, WA). The mission of the lab is to develop and apply new technologies in genomics and molecular biology. Most projects in the lab exploit new DNA sequencing technologies (Shendure et al., Nature Reviews Genetics 2004; Shendure &amp; Ji, Nature Biotechnology 2008; Shendure &amp; Lieberman Aiden, Nature Biotechnology 2012), and generally fall into one of six areas: 1) next-generation human genetics; 2) genome contiguity &amp; completeness; 3) massively parallel functional analysis; 4) molecular tagging; 5) synthetic biology; 6) translational genomics. Our interests in each of these areas are outlined briefly below, and a full list of publications is available via PubMed. http://www.ncbi.nlm.nih.gov/pubmed?cmd=search&amp;term=shendure<br />More http://krishna.gs.washington.edu/research.html</p>

<p>Lab page @ http://krishna.gs.washington.edu/index.html</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34195/strand-life-sciences-announces-the-release-of-strand-ngs-v31-at-ashg-2017</guid>
	<pubDate>Mon, 23 Oct 2017 02:36:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34195/strand-life-sciences-announces-the-release-of-strand-ngs-v31-at-ashg-2017</link>
	<title><![CDATA[Strand Life Sciences announces the release of Strand NGS v3.1 at ASHG 2017]]></title>
	<description><![CDATA[<h1><a href="http://www.strand-ngs.com/strand-announce-strandngss-v31">Strand Life Sciences announces the release of Strand NGS v3.1 at ASHG 2017</a></h1>
<p><strong><em>ORLANDO, USA, Oct 17, 2017/ PRNewswire/</em></strong></p>
<p><em>Strand NGS now supports large scale RNA- and small-RNA-Seq and Unique Molecular Identifiers (UMIs) for DNA-, RNA-, and small-RNA-Seq.</em></p>
<p>Strand Life Sciences announced the latest version release of its bioinformatics flagship product, Strand NGS, at the Annual Meeting of the American Society of Human Genetics today. Two major themes in Strand NGS v3.1 address recent challenges in next generation sequencing (NGS).</p>
<p>The first theme is large-scale RNA-Seq data analysis. Current cross-cohort RNA- and small-RNA-Seq studies span tens of replicates and batches across hundreds of samples, sometimes conducted across several different institutions. For such studies, Strand NGS v3.1 includes confounding variable analysis to eliminate technical effects, including batch effects; the t-SNE plot; profile and heat-map plots of gene-body coverage; and several other notable visual enhancements.</p>
<p>The second new feature is support for Unique Molecular Identifiers, or UMIs, for DNA-, RNA- and small-RNA-Seq. UMI support in Strand NGS is end-to-end, spanning alignment to variant calling in DNA-Seq, and alignment to quantification in RNA- and small-RNA-Seq. The Bioo Scientific, Qiagen, and Rubicon UMI protocols are natively supported, and an intuitive interface allows the specification of custom UMI protocols.</p>
<p><em>&ldquo;For liquid biopsies and low-grade FFPE samples, UMI support in DNA-Seq enables the detection of somatic variants at low concentrations. In RNA-Seq, large-scale and UMI support can be used in single-cell-based studies that reveal tumor-cell heterogeneity, even at low concentrations&rdquo;, says<strong>&nbsp;Dr. Vamsi Veeramachaneni, Chief Scientific Officer, Strand Life Sciences.</strong></em></p>
<p><em>&ldquo;At Strand, we are continuously working towards improving the accuracy and efficiency of NGS data analysis. Customers can look forward to Strand NGS becoming available on the cloud in the near future&rdquo;, says&nbsp;<strong>Dr. Ramesh Hariharan, Chief Executive Officer, Strand Life Sciences.</strong></em></p>
<p>Visit Strand Life Sciences at ASHG booth #1017 to know more about Strand NGS v3.1 and other products and service offerings from Strand Life Sciences. Click here to access detailed agenda and v3.1&nbsp;<a href="http://www.strand-ngs.com/download/releasenotes">release notes</a>.</p>
<p><strong>About Strand Life Sciences</strong></p>
<p>Strand Life Sciences is a premier life science informatics innovation company. Founded in 2000, Strand is a leader in technology innovations for healthcare using genomics. By enhancing sequence-based diagnostics and clinical genomic data interpretation using a strong foundation of computational, scientific, and medical expertise, Strand is bringing individualized medicine to the world. To know more, visit&nbsp;<a href="http://www.strandls.com/" title="www.strandls.com">www.strandls.com</a></p><p>Address of the bookmark: <a href="http://www.strand-ngs.com/strand-announce-strandngss-v31" rel="nofollow">http://www.strand-ngs.com/strand-announce-strandngss-v31</a></p>]]></description>
	<dc:creator>Yeshodari</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5661/shankar-lab</guid>
  <pubDate>Wed, 16 Oct 2013 07:02:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Shankar Lab]]></title>
  <description><![CDATA[
<p>Research Interest:</p>

<p>(A) Regulatory System Analysis with respect to microRNAs</p>

<p>(B) Computational Epigenomics &amp; Regulomics:</p>

<p>(C) Computational issues with Next Generation Sequencing:</p>

<p>Department of Biotechnology, <br />Institute of Himalyan Bioresources Technology<br />CSIR, Palampur(Himachal Pradesh), India.<br />Email: ravishihbt.res.in; ravish9gmail.com</p>

<p>More @ http://scbb.ihbt.res.in/SCBB_dept/Lab_Member.php</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41843/stringtie-transcript-assembly-and-quantification-for-rna-seq</guid>
	<pubDate>Tue, 09 Jun 2020 05:21:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41843/stringtie-transcript-assembly-and-quantification-for-rna-seq</link>
	<title><![CDATA[StringTie Transcript assembly and quantification for RNA-Seq]]></title>
	<description><![CDATA[<p><strong>StringTie</strong><span>&nbsp;is a fast and highly efficient assembler of RNA-Seq alignments into potential transcripts. It uses a novel network flow algorithm as well as an optional&nbsp;</span><em>de novo</em><span>&nbsp;assembly step to assemble and quantitate full-length transcripts representing multiple splice variants for each gene locus. Its input can include not only alignments of short reads that can also be used by other transcript assemblers, but also alignments of longer sequences that have been assembled from those reads. In order to identify differentially expressed genes between experiments, StringTie's output can be processed by specialized software like&nbsp;</span><a href="https://github.com/alyssafrazee/ballgown">Ballgown</a><span>,&nbsp;</span><a href="http://cole-trapnell-lab.github.io/cufflinks/cuffdiff/index.html">Cuffdiff</a><span>&nbsp;or other programs (DESeq2, edgeR, etc.).</span></p><p>Address of the bookmark: <a href="https://ccb.jhu.edu/software/stringtie/" rel="nofollow">https://ccb.jhu.edu/software/stringtie/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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