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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/19636?offset=150</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</guid>
	<pubDate>Tue, 16 Aug 2016 08:34:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</link>
	<title><![CDATA[KisSplice]]></title>
	<description><![CDATA[<p>KisSplice is a software that enables to analyse RNA-seq data with or without a reference genome. It is an exact local transcriptome assembler that allows to identify SNPs, indels and alternative splicing events. It can deal with an arbitrary number of biological conditions, and will quantify each variant in each condition. It has been tested on Illumina datasets of up to 1G reads. Its memory consumption is around 5Gb for 100M reads.</p>
<p>KisSplice is not a full-length transcriptome assembler. This means that it will output the variable regions of the transcripts, not reconstruct them entirely.</p>
<p>KisSplice comes as a workflow, with several possible post-treatments meant to facilitate the analysis of the results. The choice of the post-treatment depends on the availability of a reference genome/transcriptome and on the need to perform a differential analysis, as summarised in the following table.</p><p>Address of the bookmark: <a href="http://kissplice.prabi.fr/" rel="nofollow">http://kissplice.prabi.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28835/a5-miseq</guid>
	<pubDate>Thu, 18 Aug 2016 04:05:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28835/a5-miseq</link>
	<title><![CDATA[A5-miseq]]></title>
	<description><![CDATA[<p><span><span>_A5-miseq_ is a pipeline for assembling DNA sequence data generated on the Illumina sequencing platform. This README will take you through the steps necessary for running _A5-miseq_. </span></span></p>
<p><span>Point to note:</span></p>
<p><span>There are many situations where A5-miseq is not the right tool for the job. In order to produce accurate results, A5-miseq requires Illumina data with certain characteristics. A5-miseq will likely not work well with Illumina reads shorter than around 80nt, or reads where the base qualities are low in all or most reads before 60nt. A5-miseq assumes it is assembling homozygous haploid genomes. Use a different assembler for metagenomes and heterozygous diploid or polyploid organisms. Use a different assembler if a tool like FastQC reports your data quality is dubious. You have been warned! Datasets consisting solely of unpaired reads are not currently supported.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/ngopt/" rel="nofollow">https://sourceforge.net/projects/ngopt/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42490/bioinformatics-scientist-%E2%80%93-icmr-computational-genomics-centre</guid>
  <pubDate>Sat, 26 Dec 2020 10:18:29 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Scientist – ICMR Computational Genomics Centre]]></title>
  <description><![CDATA[
<p>ICMR invites online applications, from Indian Citizens, up to 8th January 2020 till 5:30 PM to fill up the following post to be filled purely on a temporary basis under “ICMR Computational Genomics Centre” under Dr. Harpreet Singh, Head, Division of Biomedical Informatics (BMI), ICMR HQRS, New Delhi 110029.<br />The Terms &amp; Conditions for the post are as follows:</p>

<p>a) Scientist-B – UR (2 posts-Bioinformatics) on consolidated salary of Rs.48,000/- pm + HRA</p>

<p>b) Scientist C – UR (1 post -Bioinformatics) on consolidated salary of Rs. 51,000 pm+ HRA</p>

<p>c) Scientist B- UR (2 post-Statistics) on a consolidated salary of Rs.48,000/- pm +HRA</p>

<p>d) Computer Programmer 1 post UR &amp; 1 post SC on a consolidated salary of Rs. 32,500/- pm</p>

<p>e) Research Assistant -UR 1 post on a consolidated salary of Rs. 31,000/- pm</p>

<p>More at https://projectjobs.icmr.org.in/sccbioinformatics/uploads/recruitment/Adv_BMI_24122020.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29235/valet</guid>
	<pubDate>Thu, 22 Sep 2016 04:27:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29235/valet</link>
	<title><![CDATA[valet]]></title>
	<description><![CDATA[<div>
<div>
<div>VALET is a pipeline for performing&nbsp;<em>de novo</em>&nbsp;validation of metagenomic assemblies. VALET checks a number of properties that should hold true for a correct assembly (e.g., mate-pairs are aligned at the correct distance from each other in the assembly, the depth of coverage is fairly uniform along contigs, etc.). The violations of these invariants are reported allowing one to pinpoint areas that were potentially mis-assembled, or to compare the quality of different assemblies. For comparing multiple assemblies of the same data-sets, VALET also reports an overall estimate of the likelihood a particular assembly is correct.</div>
</div>
</div>
<div>
<div>Home Page:&nbsp;</div>
<div>
<div><a href="https://github.com/jgluck/VALET">VALET code repository</a></div>
</div>
</div><p>Address of the bookmark: <a href="https://www.cbcb.umd.edu/software/valet" rel="nofollow">https://www.cbcb.umd.edu/software/valet</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28842/repeatmodeler</guid>
	<pubDate>Thu, 18 Aug 2016 09:57:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28842/repeatmodeler</link>
	<title><![CDATA[RepeatModeler]]></title>
	<description><![CDATA[<p><span>RepeatModeler is a de-novo repeat family identification and modeling package. At the heart of RepeatModeler are two de-novo repeat finding programs ( RECON and RepeatScout ) which employ complementary computational methods for identifying repeat element boundaries and family relationships from sequence data. RepeatModeler assists in automating the runs of RECON and RepeatScout given a genomic database and uses the output to build, refine and classify consensus models of putative interspersed repeats.</span></p><p>Address of the bookmark: <a href="http://www.repeatmasker.org/RepeatModeler.html" rel="nofollow">http://www.repeatmasker.org/RepeatModeler.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29208/srf-bioinformatics-job-position-in-national-institute-of-plant-genome-research-nipgr</guid>
  <pubDate>Mon, 19 Sep 2016 05:43:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)]]></title>
  <description><![CDATA[
<p>SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)<br />Title : “Transcriptome and small RNA diversity analysis of developing seed contrasting rice varieties” <br />Qualification : Candidates having M.Sc./M.Tech. degree or equivalent (with minimum 60% marks) in Bioinformatics with a minimum of two years of post M.Sc./M.Tech research experience are eligible to apply.<br />No. of Post : 01<br />How to apply<br />Application should reach to Dr. Pinky Agarwal, Staff Scientist, National Institute of Plant Genome Research (NIPGR) Aruna Asaf Ali Marg, P.O. Box NO. 10531, New Delhi - 110067 on or before 30/09/2016</p>

<p>More at http://www.nipgr.res.in/careers/vacancies_latest.php#</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28891/lumpy</guid>
	<pubDate>Thu, 25 Aug 2016 08:05:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28891/lumpy</link>
	<title><![CDATA[LUMPY]]></title>
	<description><![CDATA[<p>A probabilistic framework for structural variant discovery.</p>
<p>Ryan M Layer, Colby Chiang, Aaron R Quinlan, and Ira M Hall. 2014. "LUMPY: a Probabilistic Framework for Structural Variant Discovery." Genome Biology 15 (6): R84.&nbsp;<a href="http://dx.doi.org/10.1186/gb-2014-15-6-r84">doi:10.1186/gb-2014-15-6-r84</a>.</p>
<p>More at&nbsp;https://github.com/arq5x/lumpy-sv</p><p>Address of the bookmark: <a href="https://github.com/arq5x/lumpy-sv" rel="nofollow">https://github.com/arq5x/lumpy-sv</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28922/ka-ks-and-kaks-calculations</guid>
	<pubDate>Mon, 29 Aug 2016 11:44:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28922/ka-ks-and-kaks-calculations</link>
	<title><![CDATA[Ka, Ks and Ka/Ks calculations]]></title>
	<description><![CDATA[<p>gKaKs is a codon-based genome-level Ka/Ks computation pipeline developed and based on programs from four widely used packages: BLAT, BLASTALL (including bl2seq, formatdb and fastacmd), PAML (including codeml and yn00) and KaKs_Calculator (including 10 substitution rate estimation methods). gKaKs can automatically detect and eliminate frameshift mutations and premature stop codons to compute the substitution rates (Ka, Ks and Ka/Ks) between a well-annotated genome and a non-annotated genome or even a poorly assembled scaffold dataset. It is especially useful for newly sequenced genomes that have not been well annotated.&nbsp;</p>
<p>Look for KaKs calculation:</p>
<p>https://github.com/fumba/kaks-calculator</p>
<p>http://longlab.uchicago.edu/?q=gKaKs</p>
<p>http://www.ncbi.nlm.nih.gov/pubmed/23314322</p><p>Address of the bookmark: <a href="http://longlab.uchicago.edu/?q=gKaKs" rel="nofollow">http://longlab.uchicago.edu/?q=gKaKs</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28997/braker-pipeline-for-fully-automated-prediction-of-protein-coding-genes-with-genemark-eset-and-augustus-in-novel-eukaryotic-genomes</guid>
	<pubDate>Thu, 01 Sep 2016 08:02:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28997/braker-pipeline-for-fully-automated-prediction-of-protein-coding-genes-with-genemark-eset-and-augustus-in-novel-eukaryotic-genomes</link>
	<title><![CDATA[BRAKER: pipeline for fully automated prediction of protein coding genes with GeneMark-ES/ET and AUGUSTUS in novel eukaryotic genomes]]></title>
	<description><![CDATA[<p><span>Gene finding in eukaryotic genomes is notoriously difficult to automate. The task is to design a work flow with a minimal set of tools that would reach state-of-the-art performance across a wide range of species. GeneMark-ET is a gene prediction tool that incorporates RNA-Seq data into unsupervised training and subsequently generates ab initio gene predictions. AUGUSTUS is a gene finder that usually requires supervised training and uses information from RNA-Seq reads in the prediction step. Complementary strengths of GeneMark-ET and AUGUSTUS provided motivation for designing a new combined tool for automatic gene prediction.</span></p>
<p>http://www.ncbi.nlm.nih.gov/pubmed/26559507</p><p>Address of the bookmark: <a href="http://bioinf.uni-greifswald.de/bioinf/braker/" rel="nofollow">http://bioinf.uni-greifswald.de/bioinf/braker/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29112/sybil</guid>
	<pubDate>Wed, 07 Sep 2016 03:20:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29112/sybil</link>
	<title><![CDATA[Sybil]]></title>
	<description><![CDATA[<p><span>The Sybil software package provides a primarily web-based front-end to comparative genome datasets warehoused in a chado relational database. It was developed by the bioinformatics department at The Institute for Genomic Research (</span><a href="http://www.tigr.org/">TIGR</a><span>) and development continues at the J. Craig Venter Institute (</span><a href="http://jcvi.org/">JCVI</a><span>) and the Institute for Genome Sciences (</span><a href="http://igs.umaryland.edu/">IGS</a><span>) at the University of Maryland: Baltimore. Sybil has been used at TIGR/JCVI, IGS, NYU, New York Medical College, Novartis Vaccines and University of Maryland: College Park to support a number of research projects that involve comparative genome analysis. The following sections provide some high-level technical details about the overall architecture and external dependencies of the Sybil package.</span></p><p>Address of the bookmark: <a href="http://sybil.sourceforge.net/" rel="nofollow">http://sybil.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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