<?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/32709?offset=1180</link>
	<atom:link href="https://bioinformaticsonline.com/related/32709?offset=1180" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41959/rna-bloom-a-fast-and-memory-efficient-de-novo-transcript-sequence-assembler</guid>
	<pubDate>Thu, 09 Jul 2020 03:13:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41959/rna-bloom-a-fast-and-memory-efficient-de-novo-transcript-sequence-assembler</link>
	<title><![CDATA[RNA-Bloom: a fast and memory-efficient de novo transcript sequence assembler]]></title>
	<description><![CDATA[<p><strong>RNA-Bloom</strong><span>&nbsp;</span>is a fast and memory-efficient<span>&nbsp;</span><em>de novo</em><span>&nbsp;</span>transcript sequence assembler. It is designed for the following sequencing data types:</p>
<ul>
<li>single-end/paired-end bulk RNA-seq (strand-specific/agnostic)</li>
<li>paired-end single-cell RNA-seq (strand-specific/agnostic)</li>
<li>nanopore RNA-seq (PCR cDNA/direct cDNA/direct RNA)</li>
</ul>
<p>Written by<span>&nbsp;</span><a>Ka Ming Nip</a><span>&nbsp;</span>✉️</p><p>Address of the bookmark: <a href="https://github.com/bcgsc/RNA-Bloom" rel="nofollow">https://github.com/bcgsc/RNA-Bloom</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28851/senior-manager-bioinformatics-operations-at-rgcb-india</guid>
  <pubDate>Fri, 19 Aug 2016 04:37:17 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Manager (Bioinformatics Operations) at RGCB, India]]></title>
  <description><![CDATA[
<p>Senior Manager (Bioinformatics Operations) <br />Rajiv Gandhi Centre for Biotechnology (RGCB) - Thiruvananthapuram, Kerala <br />₹15,600 - ₹39,100 a month<br />Rajiv Gandhi Centre for Biotechnology (RGCB) invites applications for the following positions from Indian citizens with prescribed qualifications </p>

<p>Senior Manager (Bioinformatics Operations) <br />No. of posts: 01 (General) <br />Pay Scale: PB-3 15600-39100 + Grade Pay Rs.6600/- <br />Min. Qualification: PhD in Bioinformatics, , Life Sciences or Computer Science applied to biological questions. <br />A Min. 5 years of experience <br />Age limit: 40 years as on August 01, 2016</p>

<p>More at http://www.rgcb.res.in/positions.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34246/unicycler-hybrid-assembly-pipeline-for-bacterial-genomes</guid>
	<pubDate>Fri, 10 Nov 2017 03:58:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34246/unicycler-hybrid-assembly-pipeline-for-bacterial-genomes</link>
	<title><![CDATA[Unicycler: Hybrid assembly pipeline for bacterial genomes]]></title>
	<description><![CDATA[<p><span>Unicycler is an assembly pipeline for bacterial genomes. It can assemble&nbsp;</span><a href="http://www.illumina.com/">Illumina</a><span>-only read sets where it functions as a&nbsp;</span><a href="http://cab.spbu.ru/software/spades/">SPAdes</a><span>-optimiser. It can also assembly long-read-only sets (</span><a href="http://www.pacb.com/">PacBio</a><span>&nbsp;or&nbsp;</span><a href="https://nanoporetech.com/">Nanopore</a><span>) where it runs a&nbsp;</span><a href="https://github.com/lh3/miniasm">miniasm</a><span>+</span><a href="https://github.com/isovic/racon">Racon</a><span>&nbsp;pipeline. For the best possible assemblies, give it both Illumina reads&nbsp;</span><em>and</em><span>&nbsp;long reads, and it will conduct a hybrid assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/rrwick/Unicycler" rel="nofollow">https://github.com/rrwick/Unicycler</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37221/asplice-a-scalable-and-memory-efficient-algorithm-for-de-novo-transcriptome-assembly</guid>
	<pubDate>Tue, 03 Jul 2018 04:09:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37221/asplice-a-scalable-and-memory-efficient-algorithm-for-de-novo-transcriptome-assembly</link>
	<title><![CDATA[ASplice: a scalable and memory-efficient algorithm for de novo transcriptome assembly]]></title>
	<description><![CDATA[With increased availability of de novo assembly algorithms, it is feasible to study entire transcriptomes of non-model organisms. While algorithms are available that are specifically designed for performing transcriptome assembly from high-throughput sequencing data, they are very memory-intensive, limiting their applications to small data sets with few libraries.

Texas A&amp;M University researchers develop a transcriptome assembly algorithm that recovers alternatively spliced isoforms and expression levels while utilizing as many RNA-Seq libraries as possible that contain hundreds of gigabases of data. New techniques are developed so that computations can be performed on a computing cluster with moderate amount of physical memory.

Availability – A software program that implements the algorithm is available at: http://faculty.cse.tamu.edu/shsze/asplice.

Sze SH, Pimsler ML, Tomberlin JK, Jones CD, Tarone AM. (2017) A scalable and memory-efficient algorithm for de novo transcriptome assembly of non-model organisms. BMC Genomics 18(Suppl 4):387.<p>Address of the bookmark: <a href="http://faculty.cse.tamu.edu/shsze/asplice/" rel="nofollow">http://faculty.cse.tamu.edu/shsze/asplice/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29263/srf-bioinformatics-at-bose-institute-india</guid>
  <pubDate>Thu, 29 Sep 2016 09:39:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF Bioinformatics at Bose Institute, India]]></title>
  <description><![CDATA[
<p>Advt. No. S/DPB(CB)/17/2016-17 <br />Junior Research Assistant/ Senior Research Assistant  Job vacancies in Bose Institute on temporary basis<br />Project Title : “Genome wide transcriptome analysis to identity MYMIV-stress related genomic resources of blackgram”<br />Junior Research Assistant <br />Qualification : Good academic record in B.Sc. and M.Sc. in Botany or Biotechnology from reputed Universities. Must have good practical hand, this should be certified by two Senior/reputed PG teachers on a scale of 10. <br />Desirable : Preference will be given to those who already have some research experience (for at least 2 months). <br />Consolidated Pay : Rs. 16,400/- p.m. <br />Age Limit : Below 28 years (relaxable in case of SC/ST/OBC/Women candidates only as per rules).<br />Senior Research Assistant <br />Qualification : B.Sc. in Biotechnology and M.Sc. in Biotechnology or Bioinformatics. Hands on training in Bioinformatics. At least two Research Publications with Bioinformatics components. <br />Desirable : Preference will be given to the candidates who have previous experience in Next Gen Sequencing data analysis of genomic/transcriptome/miRNA. <br />Consolidated Pay : Rs. 18,700/- p.m.  <br />Age Limit : Below 30 years (relaxable in case of SC/ST/OBC/Women candidates only as per rules).</p>

<p>http://www.boseinst.ernet.in/advertisement.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</guid>
	<pubDate>Wed, 14 Nov 2018 04:50:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</link>
	<title><![CDATA[MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph]]></title>
	<description><![CDATA[<p><span>MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct&nbsp;</span><em>de Bruijn</em><span>&nbsp;graph (SdBG) to achieve low memory assembly. MEGAHIT can&nbsp;</span><span>optionally</span><span>&nbsp;utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. MEGAHIT v1.0 or greater also supports IBM Power PC and has been tested on IBM POWER8.</span></p>
<p><span>https://academic.oup.com/bioinformatics/article/31/10/1674/177884</span></p><p>Address of the bookmark: <a href="https://github.com/voutcn/megahit" rel="nofollow">https://github.com/voutcn/megahit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29410/entrez-direct-e-utilities-on-the-unix-command-line</guid>
	<pubDate>Wed, 19 Oct 2016 08:06:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29410/entrez-direct-e-utilities-on-the-unix-command-line</link>
	<title><![CDATA[Entrez Direct: E-utilities on the UNIX Command Line]]></title>
	<description><![CDATA[<p>Entrez Direct (EDirect) is an advanced method for accessing the NCBI's suite of interconnected databases (publication, sequence, structure, gene, variation, expression, etc.) from a UNIX terminal window. Functions take search terms from command-line arguments. Individual operations are combined to build multi-step queries. Record retrieval and formatting normally complete the process.</p>
<p>EDirect also provides an argument-driven function that simplifies the extraction of data from document summaries or other results that are returned in structured XML format. This can eliminate the need for writing custom software to answer ad hoc questions. Queries can move seamlessly between EDirect commands and UNIX utilities or scripts to perform actions that cannot be accomplished entirely within Entrez.</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/books/NBK179288/" rel="nofollow">https://www.ncbi.nlm.nih.gov/books/NBK179288/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29578/plink2</guid>
	<pubDate>Thu, 27 Oct 2016 11:24:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29578/plink2</link>
	<title><![CDATA[PLINK2]]></title>
	<description><![CDATA[<p><span>This is a comprehensive update to Shaun Purcell's&nbsp;</span><a href="http://pngu.mgh.harvard.edu/~purcell/plink/">PLINK</a><span>&nbsp;command-line program, developed by&nbsp;</span><a href="mailto:chrchang@alumni.caltech.edu">Christopher Chang</a><span>&nbsp;with support from the&nbsp;</span><a href="http://www.niddk.nih.gov/">NIH-NIDDK</a><span>'s Laboratory of Biological Modeling, the&nbsp;</span><a href="http://research.mssm.edu/statgen/">Purcell Lab</a><span>&nbsp;at Mount Sinai School of Medicine, and others. (</span><a href="https://www.cog-genomics.org/plink2/#new">What's new?</a><span>) (</span><a href="https://www.cog-genomics.org/plink2/credits">Credits.</a><span>) (</span><a href="http://www.gigasciencejournal.com/content/4/1/7">Methods paper.</a><span>)</span></p><p>Address of the bookmark: <a href="https://www.cog-genomics.org/plink2/" rel="nofollow">https://www.cog-genomics.org/plink2/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39098/sda-long-read-sequence-and-assembly-of-segmental-duplications</guid>
	<pubDate>Tue, 05 Mar 2019 10:00:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39098/sda-long-read-sequence-and-assembly-of-segmental-duplications</link>
	<title><![CDATA[SDA: Long-read sequence and assembly of segmental duplications]]></title>
	<description><![CDATA[<p><span><span>Segmental Duplication Assembler (SDA; https://github.com/mvollger/SDA) constructs graphs in which paralogous sequence variants define the nodes and long-read sequences provide attraction and repulsion edges, enabling the partition and assembly of long reads corresponding to distinct paralogs.<br></span></span></p>
<p><span><span>https://github.com/mvollger/SDA</span></span></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/s41592-018-0236-3" rel="nofollow">https://www.nature.com/articles/s41592-018-0236-3</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>

</channel>
</rss>