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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27090?offset=1010</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28577/research-associate-computer-sciences-recruitment-in-national-bureau-of-plant-genetic-resources</guid>
  <pubDate>Thu, 28 Jul 2016 04:39:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate (Computer Sciences) recruitment in National Bureau of Plant Genetic Resources]]></title>
  <description><![CDATA[
<p>Research Associate (Computer Sciences) recruitment in National Bureau of Plant Genetic Resources</p>

<p>Project: Indo-UK Centre for improvement of Nitrogen use efficiency in wheat Dr. Soma S. Marla, Pr. Scientist (Bioinformatics), Division of Genomic Resources, ICAR, NBPGR, ND.</p>

<p>Qualification: Ph.D. Degree in Computer Sciences/Bioinformatics OR 1. First class Master’s degree in any discipline of Plant Sciences with specialization in Computer Sciences/ Bioinformatics having 1st division or 60% marks or equivalent overall grade point average with at least two years of research experience as evidenced from Fellowship/ Associate ship. 2. NET qualification is essential for the candidates with 3+2 years B.Sc.+ M.Sc. Desirable: Demonstrated experience &amp; skills in database design, management, UNIX OS, in NGS data analysis. Experience substantiated by publications of high quality will be preferred.</p>

<p>No.of Post: 1</p>

<p>Pay Scale: Rs. 40,000 (Ph.D)/ Rs + 30 % HRA; Rs.38,000 ( Masters Degree 0 + 30 % HRA).</p>

<p>Age Limit : below 40 years for RA position<br />How to apply<br />Applicants for RA post should send their complete CV (Advance copy of the application may be sent by email to :soma.marla@icar.gov.in or ssmarl@yahoo.com, should enclose the copy of the research publications; one page summary of their achievement relevant to the post applied for; and should enclose two reference letters (one must be from the person with whom worked latest). Shortlisted candidate will be intimated for interview by email.</p>

<p>The candidates who wish to attend the walk-in interview are requested to bring with them five copies of the CV (one copy with photograph) as per the format given below. Also, the candidates should bring the original documents such as degree certificates, marks sheets, publications, thesis, experience certificate etc. for verification. </p>

<p>Date of Interview: 17.8.2016.</p>

<p>More at http://www.nbpgr.ernet.in/Downloadfile.aspx?EntryId=7133</p>
]]></description>
</item>
<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>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28618/jrf-bioinformatics-at-dpu-india</guid>
  <pubDate>Fri, 05 Aug 2016 03:06:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics at DPU, India]]></title>
  <description><![CDATA[
<p>Advertisement for position of “JRF (Junior Research Fellow)” on DST research project “Molecular modeling and docking studies on Deguelin and its derivatives with cell cycle arrest, apoptosis and anti-angiogenesis pathway proteins in cancer cell signaling pathway”</p>

<p>Applications are invited on plain paper from eligible candidates along with biodata and copies of certificates in support of age, qualification and experience for the following position:</p>

<p>Particulars Description</p>

<p>1. Position &amp; No. JRF (Junior Research Fellow) 01</p>

<p>2. Title of the Project Molecular modeling and docking studies on Deguelin and its derivatives with cell cycle arrest, apoptosis and anti-angiogenesis pathway proteins in cancer cell signaling pathway</p>

<p>3. Tenure 3 years</p>

<p>4. Investigator Dr. K. V.Swamy</p>

<p>5. Institute Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Tathawade, Pune 411033.</p>

<p>5. Qualifications/Eligibility</p>

<p>Essential: NET (National Eligibility Test) qualified M. Sc Bioinformatics/ M. Tech Bioinformatics/M. Sc Biotechnology/M. Tech Biotechnology or Graduate degree in Professional course with NET qualification or Post graduation degree in professional course</p>

<p>The following examinations conducted by various Central Government Departments/Agencies are considered as National Eligibility Test (NET).</p>

<p>1. CSIR-UGC-LS <br />2. GATE (Graduate Aptitude Test in Engineering) <br />3. JAM (Joint Admission Test) <br />4. GPAT (Graduate Pharmacy Aptitude Test) <br />5. BET(Biotechnology Eligibility Test) <br />6. BINC(Bioinformatics National Consortium) <br />7. JEST( Joint Entrance Screening Test) <br />8. JGEEBILS(Joint Graduate Entrance Examination for Biology &amp; Interdisciplinary Life Sciences) <br />9. NBHM Ph.D scholarship Screening Test <br />10. ICMR- JRF Entrance Examination <br />11. AICE (ICAR-All India competitive Examination ) <br />(For all above examinations valid score considered at the time of interview)</p>

<p>Desirable: Knowledge and skills in Bioinformatics tools/ softwares</p>

<p>6. Monthly Emoluments Rs.25,000/ (As per DST-SERB rules)</p>

<p>7. Last date for submission of prescribed application 20/08/2016</p>

<p>Kindly send your applications to “Dr. K. V. Swamy, Asst.Professor, Dr. D. Y. Patil Biotechnology &amp; Bioinformatics Institute, Survey No. 87/88, Mumbai-Pune Express Way, Tathawade, Pune - 411033, Maharashtra, India”. Highlight the envelope with “Application for post of JRF (Junior Research Fellow)”.</p>

<p>Note: No TA/DA will be paid for attending the interview.</p>

<p>Advertisement: http://careers.dpu.edu.in/Biotech.aspx</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37962/wtdbg2-a-de-novo-sequence-assembler-for-long-noisy-reads-produced-by-pacbio-or-oxford-nanopore</guid>
	<pubDate>Fri, 19 Oct 2018 08:48:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37962/wtdbg2-a-de-novo-sequence-assembler-for-long-noisy-reads-produced-by-pacbio-or-oxford-nanopore</link>
	<title><![CDATA[Wtdbg2: a de novo sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore]]></title>
	<description><![CDATA[<p><span>Wtdbg2 is a&nbsp;</span><em>de novo</em><span>&nbsp;sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output. Wtdbg2 is able to assemble the human and even the 32Gb&nbsp;</span><a href="https://www.nature.com/articles/nature25458">Axolotl</a><span>&nbsp;genome at a speed tens of times faster than&nbsp;</span><a href="https://github.com/marbl/canu">CANU</a><span>&nbsp;and&nbsp;</span><a href="https://github.com/PacificBiosciences/FALCON">FALCON</a><span>while producing contigs of comparable base accuracy.</span></p><p>Address of the bookmark: <a href="https://github.com/ruanjue/wtdbg2" rel="nofollow">https://github.com/ruanjue/wtdbg2</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40510/reps-repeat-masked-phrap-with-scaffolding-a-wgs-sequence-assembler</guid>
	<pubDate>Sat, 04 Jan 2020 01:08:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40510/reps-repeat-masked-phrap-with-scaffolding-a-wgs-sequence-assembler</link>
	<title><![CDATA[RePS: Repeat-masked Phrap with scaffolding, a WGS sequence assembler]]></title>
	<description><![CDATA[<p>RePS (Repeat-masked Phrap with scaffolding), a WGS sequence assembler, that explicitly identifies exact kmer repeats from the shotgun data and removes them prior to the assembly. The established software Phrap is used to compute meaningful error probabilities for each base. Clone-end-pairing information is used to construct scaffolds that order and orient the contigs. The updated version of RePS incorporates some of the ideas introduced by Phusion on clustering</p>
<p><img src="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/bin/45793-17f1_F4TT.jpg" alt="image" style="border: 0px;"></p>
<p>More at</p>
<p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/</a></p><p>Address of the bookmark: <a href="ftp://ftp.genomics.org.cn/pub/ricedb/Tools/RePS/RePS-IBM-AIX.tar.gz" rel="nofollow">ftp://ftp.genomics.org.cn/pub/ricedb/Tools/RePS/RePS-IBM-AIX.tar.gz</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28802/research-associate-bioinformatics-recruitment-in-icgeb-new-delhi</guid>
  <pubDate>Tue, 16 Aug 2016 03:38:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate Bioinformatics recruitment in ICGEB, New Delhi]]></title>
  <description><![CDATA[
<p>Research Associate Bioinformatics recruitment in ICGEB, New Delhi </p>

<p>Project :“Genetic Transformation and Development of Elite Transgenic Maize (Zea mays L.) for Biotic and Abiotic Stresses Tolerance”.</p>

<p>Qualification: Ph.D. degree in:Biotechnology/Bioinformatics/Biochemistry/Plant Molecular Biology/Plant Physiology/Botany or any related area with evidence of prior experience in maize transformation.</p>

<p>Additional experience in plant transformation of any cereal crop would be preferable.</p>

<p>The appointment would initially be for one year.</p>

<p>How to apply<br />Interested applicants should send their detailed CV including brief synopsis regarding the previous research experience (along withcontact email address by email) to: Dr. Tanushri Kaul (tanushri@icgeb.res.in). Group Leader, Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi-110 067.</p>

<p>Closing date for applications: 22 August 2016.</p>

<p>More at http://www.icgeb.org/vacancies.html</p>
]]></description>
</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/33847/omega2-metagenome-assembly-pipeline</guid>
	<pubDate>Mon, 10 Jul 2017 05:56:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33847/omega2-metagenome-assembly-pipeline</link>
	<title><![CDATA[Omega2: metagenome assembly pipeline]]></title>
	<description><![CDATA[<p><span>Omega found overlaps between reads using a prefix/suffix hash table. The overlap graph of reads was simplified by removing transitive edges and trimming short branches. Unitigs were generated based on minimum cost flow analysis of the overlap graph and then merged to contigs and scaffolds using mate-pair information. In comparison with three de Bruijn graph assemblers (SOAPdenovo, IDBA-UD and MetaVelvet), Omega provided comparable overall performance on a HiSeq 100-bp dataset and superior performance on a MiSeq 300-bp dataset. In comparison with Celera on the MiSeq dataset, Omega provided more continuous assemblies overall using a fraction of the computing time of existing overlap-layout-consensus assemblers. This indicates Omega can more efficiently assemble longer Illumina reads, and at deeper coverage, for metagenomic datasets.</span></p><p>Address of the bookmark: <a href="http://omega.omicsbio.org/" rel="nofollow">http://omega.omicsbio.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34416/miniasm-very-fast-olc-based-de-novo-assembler-for-noisy-long-reads</guid>
	<pubDate>Mon, 27 Nov 2017 07:58:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34416/miniasm-very-fast-olc-based-de-novo-assembler-for-noisy-long-reads</link>
	<title><![CDATA[miniasm: very fast OLC-based de novo assembler for noisy long reads]]></title>
	<description><![CDATA[<p>Miniasm is a very fast OLC-based&nbsp;<em>de novo</em>&nbsp;assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>) as input and outputs an assembly graph in the&nbsp;<a href="https://github.com/pmelsted/GFA-spec/blob/master/GFA-spec.md">GFA</a>&nbsp;format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Celera_Assembler_Terminology">unitig</a>&nbsp;sequences. Thus the per-base error rate is similar to the raw input reads.</p>
<p>So far miniasm is in early development stage. It has only been tested on a dozen of PacBio and Oxford Nanopore (ONT) bacterial data sets. Including the mapping step, it takes about 3 minutes to assemble a bacterial genome. Under the default setting, miniasm assembles 9 out of 12 PacBio datasets and 3 out of 4 ONT datasets into a single contig. The 12 PacBio data sets are&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/E.-coli-Bacterial-Assembly">PacBio E. coli sample</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS473430">ERS473430</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS544009">ERS544009</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS554120">ERS554120</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS605484">ERS605484</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS617393">ERS617393</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS646601">ERS646601</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS659581">ERS659581</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS670327">ERS670327</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS685285">ERS685285</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS743109">ERS743109</a>&nbsp;and a&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/E.-coli-20kb-Size-Selected-Library-with-P6-C4/ce0533c1d2a957488594f0b29da61ffa3e4627e8">deprecated PacBio E. coli data set</a>. ONT data are acquired from the&nbsp;<a href="http://lab.loman.net/2015/09/24/first-sqk-map-006-experiment/">Loman Lab</a>.</p>
<p>For a&nbsp;<em>C. elegans</em>&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/C.-elegans-data-set">PacBio data set</a>&nbsp;(only 40X are used, not the whole dataset), miniasm finishes the assembly, including reads overlapping, in ~10 minutes with 16 CPUs. The total assembly size is 105Mb; the N50 is 1.94Mb. In comparison, the&nbsp;<a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/HGAP">HGAP3</a>produces a 104Mb assembly with N50 1.61Mb.&nbsp;<a href="http://lh3lh3.users.sourceforge.net/download/ce-miniasm.png">This dotter plot</a>&nbsp;gives a global view of the miniasm assembly (on the X axis) and the HGAP3 assembly (on Y). They are broadly comparable. Of course, the HGAP3 consensus sequences are much more accurate. In addition, on the whole data set (assembled in ~30 min), the miniasm N50 is reduced to 1.79Mb. Miniasm still needs improvements.</p>
<p>Miniasm confirms that at least for high-coverage bacterial genomes, it is possible to generate long contigs from raw PacBio or ONT reads without error correction. It also shows that&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>&nbsp;can be used as a read overlapper, even though it is probably not as sensitive as the more sophisticated overlapers such as&nbsp;<a href="https://github.com/marbl/MHAP">MHAP</a>&nbsp;and&nbsp;<a href="https://github.com/thegenemyers/DALIGNER">DALIGNER</a>. Coupled with long-read error correctors and consensus tools, miniasm may also be useful to produce high-quality assemblies.</p>
<p>Minimap and miniasm are ultrafast tools for (i) mapping and (ii) assembly. Designed for long, noisy reads, they do not have a correction or consensus step, and therefore the resulting assemblies are contiguous (i.e. long) but very noisy (i.e. full of errors)</p>
<p>We start with an all against all comparison:</p>
<div>
<pre><code>minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq | gzip -1 &gt; reads.paf.gz
</code></pre>
</div>
<p>Then we can assemble</p>
<div>
<pre><code>miniasm -f reads.fq reads.paf.gz &gt; reads.gfa
</code></pre>
</div>
<p>Convert GFA to FASTA:</p>
<div>
<pre><code>awk <span>'/^S/{print "&gt;"$2"\n"$3}'</span> reads.gfa | fold &gt; reads.fa
</code></pre>
</div>
<p>And then count how many contigs:</p>
<div>
<pre><code>grep <span>"&gt;"</span> reads.fa | wc -l</code></pre>
</div>
<p>&nbsp;</p>
<pre><span><span>#</span> Download sample PacBio from the PBcR website</span>
wget -O- http://www.cbcb.umd.edu/software/PBcR/data/selfSampleData.tar.gz <span>|</span> tar zxf -
ln -s selfSampleData/pacbio_filtered.fastq reads.fq
<span><span>#</span> Install minimap and miniasm (requiring gcc and zlib)</span>
git clone https://github.com/lh3/minimap <span>&amp;&amp;</span> (cd minimap <span>&amp;&amp;</span> make)
git clone https://github.com/lh3/miniasm <span>&amp;&amp;</span> (cd miniasm <span>&amp;&amp;</span> make)
<span><span>#</span> Overlap</span>
minimap/minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq <span>|</span> gzip -1 <span>&gt;</span> reads.paf.gz
<span><span>#</span> Layout</span>
miniasm/miniasm -f reads.fq reads.paf.gz <span>&gt;</span> reads.gfa</pre><p>Address of the bookmark: <a href="https://github.com/lh3/miniasm" rel="nofollow">https://github.com/lh3/miniasm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36621/hapcut2-robust-and-accurate-haplotype-assembly-for-diverse-sequencing-technologies</guid>
	<pubDate>Tue, 15 May 2018 07:35:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36621/hapcut2-robust-and-accurate-haplotype-assembly-for-diverse-sequencing-technologies</link>
	<title><![CDATA[HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies]]></title>
	<description><![CDATA[HapCUT2 is a maximum-likelihood-based tool for assembling haplotypes from DNA sequence reads, designed to "just work" with excellent speed and accuracy. We found that previously described haplotype assembly methods are specialized for specific read technologies or protocols, with slow or inaccurate performance on others. With this in mind, HapCUT2 is designed for speed and accuracy across diverse sequencing technologies, including but not limited to:

NGS short reads (Illumina HiSeq)
clone-based sequencing (Fosmid or BAC clones)
SMRT reads (PacBio)
Oxford Nanopore reads
10X Genomics Linked-Reads
proximity-ligation (Hi-C) reads
high-coverage sequencing (&gt;40x coverage-per-SNP) using above technologies
combinations of the above technologies (e.g. scaffold long reads with Hi-C reads)
See below for specific examples of command line options and best practices for some of these technologies.

NOTE: At this time HapCUT2 is for diploid organisms only. VCF input should contain diploid variants.

If you use HapCUT2 in your research, please cite:

Edge, P., Bafna, V. &amp; Bansal, V. HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies. Genome Res. gr.213462.116 (2016). doi:10.1101/gr.213462.116<p>Address of the bookmark: <a href="https://github.com/vibansal/HapCUT2" rel="nofollow">https://github.com/vibansal/HapCUT2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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