<?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/32730?offset=1450</link>
	<atom:link href="https://bioinformaticsonline.com/related/32730?offset=1450" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30557/speedseq</guid>
	<pubDate>Fri, 20 Jan 2017 06:05:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30557/speedseq</link>
	<title><![CDATA[SpeedSeq]]></title>
	<description><![CDATA[<p>A flexible framework for rapid genome analysis and interpretation</p>
<p>C Chiang, R M Layer, G G Faust, M R Lindberg, D B Rose, E P Garrison, G T Marth, A R Quinlan, and I M Hall. SpeedSeq: ultra-fast personal genome analysis and interpretation. Nat Meth (2015). doi:10.1038/nmeth.3505.</p>
<p><a href="http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3505.html">http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3505.html</a></p><p>Address of the bookmark: <a href="https://github.com/hall-lab/speedseq" rel="nofollow">https://github.com/hall-lab/speedseq</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42619/metaeuk-sensitive-high-throughput-gene-discovery-and-annotation-for-large-scale-eukaryotic-metagenomics</guid>
	<pubDate>Wed, 13 Jan 2021 19:29:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42619/metaeuk-sensitive-high-throughput-gene-discovery-and-annotation-for-large-scale-eukaryotic-metagenomics</link>
	<title><![CDATA[MetaEuk - sensitive, high-throughput gene discovery and annotation for large-scale eukaryotic metagenomics]]></title>
	<description><![CDATA[<p><span>MetaEuk is a modular toolkit designed for large-scale gene discovery and annotation in eukaryotic metagenomic contigs. Metaeuk combines the fast and sensitive homology search capabilities of&nbsp;</span><a href="https://github.com/soedinglab/MMseqs2">MMseqs2</a><span>&nbsp;with a dynamic programming procedure to recover optimal exons sets. It reduces redundancies in multiple discoveries of the same gene and resolves conflicting gene predictions on the same strand. MetaEuk is GPL-licensed open source software that is implemented in C++ and available for Linux and macOS. The software is designed to run on multiple cores.</span></p><p>Address of the bookmark: <a href="https://github.com/soedinglab/metaeuk" rel="nofollow">https://github.com/soedinglab/metaeuk</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30680/easybuild</guid>
	<pubDate>Fri, 27 Jan 2017 16:00:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30680/easybuild</link>
	<title><![CDATA[EasyBuild]]></title>
	<description><![CDATA[<p><a href="https://github.com/hpcugent/easybuild">EasyBuild</a><span>&nbsp;is a software build and installation framework that allows you to manage (scientific) software on High Performance Computing (HPC) systems in an efficient way.</span><br><span>A full list of supported software packages is available&nbsp;</span><a href="http://easybuild.readthedocs.io/en/latest/version-specific/Supported_software.html">here</a><span>.</span></p><p>Address of the bookmark: <a href="https://hpcugent.github.io/easybuild/" rel="nofollow">https://hpcugent.github.io/easybuild/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43877/crowdgo-machine-learning-and-semantic-similarity-guided-consensus-gene-ontology-annotation</guid>
	<pubDate>Thu, 26 May 2022 00:59:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43877/crowdgo-machine-learning-and-semantic-similarity-guided-consensus-gene-ontology-annotation</link>
	<title><![CDATA[CrowdGO: Machine learning and semantic similarity guided consensus Gene Ontology annotation]]></title>
	<description><![CDATA[<p dir="auto">CrowdGO is a protein Gene Ontology predictor using a meta approach, analyzing the predictions of other tools in order to get an improved precision and recall.</p>
<p dir="auto">Please note that the CrowdGO snakemake workflow is currently only tested on Ubuntu. It should work on OSX, but please report any errors to <a href="mailto:maarten.reijnders@unil.ch">maarten.reijnders@unil.ch</a> or create an issue.</p>
<p>https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010075</p><p>Address of the bookmark: <a href="https://gitlab.com/mreijnders/crowdgo" rel="nofollow">https://gitlab.com/mreijnders/crowdgo</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/30744/binc-2017</guid>
	<pubDate>Wed, 01 Feb 2017 09:36:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/30744/binc-2017</link>
	<title><![CDATA[BINC 2017]]></title>
	<description><![CDATA[<p><span>Pondicherry University,Puducherry,on behalf of Department of Biotechnology, Government of India, conducted the BINC examination in&nbsp;</span><span style="color: blue;">2015 and 2016.&nbsp;</span><span>The objective of this examination is to certify bioinformatics professionals, trained formally as well as self-trained.</span><span style="color: blue;">Registration for BINC 2017 examination will open from January 29,2017 to February 28,2017.</span><span>&nbsp;</span></p><p><span>Pondicherry University, Puducherry has been identified as a nodal agency by the Department of Biotechnology, Govt. of India to coordinate this examination along with nine centres namely, </span></p><p><span>Pune University, Pune; </span></p><p><span>Anna University, Chennai; </span></p><p><span>Bose Institute, Kolkata; </span></p><p><span>Institute of Bioinformatics &amp; Applied Biotechnology, Bangalore; </span></p><p><span>North-Eastern Hill University, Shillong, University of Hyderabad, Hyderabad; </span></p><p><span>University of Kerala, Thiruvananthapuram; </span></p><p><span>Jawaharlal Nehru University, New Delhi and </span></p><p><span>Assam Agricultural University, Guwahati.</span><span style="color: blue;"><strong>&nbsp;</strong></span></p><p><span style="color: blue;"><strong>In the BINC 2015 and 2016 examination, 23 candidates and five candidates were certified respectively.</strong></span><span>&nbsp;DBT has agreed to fund Research fellowships for all the BINC qualified Indian nationals to pursue Ph.D. in Indian Institutes/Universities. </span></p><p><span>Note that the candidate must possess a postgraduate degree(or equivalent) &amp; meet the criteria of the institutes/universities in order to avail research fellowship. </span></p><p><span>In addition, cash prize of Rs. 10,000/- will be awarded to the top 10 BINC qualifiers.</span></p><p><span>More at&nbsp;http://www.pondiuni.edu.in/exams/binc/</span></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/30874/important-journals-blogs-and-forums-for-bioinformaticians</guid>
	<pubDate>Wed, 08 Feb 2017 09:15:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/30874/important-journals-blogs-and-forums-for-bioinformaticians</link>
	<title><![CDATA[Important Journals, Blogs and Forums for Bioinformaticians]]></title>
	<description><![CDATA[<p><em>Journals</em>. Most journals have RSS feeds for their current updates.</p><ul>
<li><a href="http://bioinformatics.oxfordjournals.org/rss/" target="_blank">Bioinformatics - RSS feed of current and advance online publications</a></li>
<li><a href="http://genome.cshlp.org/rss/" target="_blank">Genome Research - current &amp; advance</a></li>
<li><a href="http://genomebiology.com/" target="_blank">Genome Biology - editors picks, latest, most viewed, most forwarded</a>. (Hit the RSS icon under each tab).</li>
<li><a href="http://www.plosgenetics.org/static/rssFeeds.action" target="_blank">PLoS Genetics - new articles</a></li>
<li><a href="http://www.ploscompbiol.org/static/rssFeeds.action" target="_blank">PLoS Computational Biology - new articles</a></li>
<li><a href="http://www.nature.com/ng/newsfeeds.html" target="_blank">Nature Genetics - current TOC and AOP</a></li>
<li><a href="http://www.nature.com/nrg/info/newsfeeds.html" target="_blank">Nature Reviews Genetics - current TOC and AOP</a></li>
</ul><ul>
<li><a href="https://academic.oup.com/bioinformatics" target="_blank">Bioinformatics</a></li>
<li><a href="https://bmcbioinformatics.biomedcentral.com/" target="_blank">BMC Bioinformatics</a></li>
<li><a href="https://academic.oup.com/bib" target="_blank">Briefings in Bioinformatics</a></li>
<li><a href="http://genomebiology.biomedcentral.com/" target="_blank">Genome Biology</a></li>
<li><a href="http://genome.cshlp.org/rss/" target="_blank">Genome Research: current and AOP</a></li>
<li><a href="http://microbiomejournal.biomedcentral.com/" target="_blank">Microbiome</a></li>
<li><a href="http://www.nature.com/ng/newsfeeds.html" target="_blank">Nature Genetics, current &amp; AOP</a></li>
<li><a href="http://www.nature.com/nrg/info/newsfeeds.html" target="_blank">Nature Reviews Genetics, current &amp; AOP</a></li>
<li><a href="https://academic.oup.com/nar" target="_blank">Nucleic Acids Research</a></li>
<li><a href="http://journals.plos.org/ploscompbiol/s/help-using-this-site#loc-article-feeds" target="_blank">PLOS Computational Biology</a></li>
<li><a href="http://journals.plos.org/plosgenetics/s/help-using-this-site#loc-article-feeds" target="_blank">PLOS Genetics</a></li>
</ul><p><em>Blogs</em><span>. Some of these blogs are very relevant to bioinfo jobs. Others are more personal interest.</span></p><ul>
<li><a href="http://blog.openhelix.eu/" target="_blank">The OpenHelix Blog</a></li>
<li><a href="http://www.ensembl.info/" target="_blank">Ensembl blog</a></li>
<li><a href="http://wiki.g2.bx.psu.edu/News" target="_blank">Galaxy News</a></li>
<li><a href="http://bcbio.wordpress.com/" target="_blank">Blue Collar Bioinformatics</a></li>
<li><a href="http://www.homolog.us/blogs/" target="_blank">Homologus</a></li>
<li><a href="http://blog.goldenhelix.com/" target="_blank">Golden Helix - our 2 SNPs</a></li>
<li><a href="http://genomicslawreport.com/" target="_blank">Genomics Law Report</a></li>
<li><a href="http://www.r-bloggers.com/" target="_blank">R-bloggers</a>&nbsp;(aggregates feeds from &gt;350 blogs about R)</li>
<li><a href="http://genomesunzipped.org/" target="_blank">Genomes Unzipped</a></li>
<li><a href="http://compgen.blogspot.com/" target="_blank">Jason Moore's Epistasis Blog</a></li>
<li><a href="http://spittoon.23andme.com/" target="_blank">23andMe - the Spitoon</a></li>
</ul><ul>
<li><a href="http://varianceexplained.org/" target="_blank">Variance Explained</a>: David Robinson&rsquo;s blog (Data Scientist at Stack Overflow, works in R and Python).</li>
<li><a href="https://globalbiodefense.com/" target="_blank">Global Biodefense</a>: News on pathogens, outbreaks, and preparedness, with periodic posts on genomics and bioinformatics-related developments and funding opportunities.</li>
<li><a href="https://flxlexblog.wordpress.com/" target="_blank">In between lines of code</a>: Lex Nederbragt&rsquo;s blog on biology, sequencing, bioinformatics, &hellip;</li>
<li><a href="http://simplystatistics.org/" target="_blank">Simply Statistics</a>: A statistics blog by Rafa Irizarry, Roger Peng, and Jeff Leek.</li>
<li><a href="https://liorpachter.wordpress.com/" target="_blank">Bits of DNA</a>: Reviews and commentary on computational biology by Lior Pachter (fair warning: dialogue here can get a bit heated!).</li>
<li><a href="http://bcb.io/articles/" target="_blank">Blue Collar Bioinformatics</a>: articles related tool validation and the open source bioinformatics community.</li>
<li><a href="https://microbiomedigest.com/" target="_blank">Microbiome Digest &ndash; Bik&rsquo;s Picks</a>: A daily digest of scientific microbiome papers, by Elisabeth Bik, Science Editor at uBiome.</li>
<li><a href="http://ivory.idyll.org/blog/" target="_blank">Living in an Ivory Basement</a>: Titus Brown&rsquo;s blog on metagenomics, open science, testing, reproducibility, and programming.</li>
<li><a href="http://enseqlopedia.com/" target="_blank">Enseqlopedia</a>: James Hadfield&rsquo;s blog on all things NGS.</li>
<li><a href="http://www.epistasisblog.org/" target="_blank">Epistasis Blog</a>: Jason Moore&rsquo;s computational biology blog.</li>
<li><a href="https://blog.rstudio.org/" target="_blank">RStudio Blog</a>: announcements about new RStudio functionality, updates about the&nbsp;<a href="http://tidyverse.org/" target="_blank">tidyverse</a>, and more.</li>
<li><a href="http://nextgenseek.com/" target="_blank">nextgenseek.com</a>: Next-Gen Sequencing Blog covering new developments in NGS data &amp; analysis.</li>
<li><a href="http://www.rna-seqblog.com/" target="_blank">RNA-Seq Blog</a>: Transcriptome Research &amp; Industry News.</li>
<li><a href="http://www.theallium.com/" target="_blank">The Allium</a>: We all need a little humor in our lives. Like&nbsp;<em>The Onion</em>, but for science.</li>
</ul><p><em>Forums.</em></p><ul>
<li><a href="http://seqanswers.com/forums/forumdisplay.php?f=18" target="_blank">Seqanswers - bioinformatics forum</a></li>
<li><a href="http://seqanswers.com/forums/forumdisplay.php?f=26" target="_blank">Seqanswers - RNA-Seq forum</a></li>
<li><a href="http://www.biostars.org/rss/" target="_blank">BioStar</a></li>
<li><a href="http://bioinformaticsonline.com/">BOL</a></li>
</ul>]]></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/opportunity/view/30928/jrf-bioinformatics-job-vacancies-in-tezpur-university</guid>
  <pubDate>Tue, 14 Feb 2017 16:40:26 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics job vacancies in Tezpur University]]></title>
  <description><![CDATA[
<p>Memo No. DoRD/CSE/SSS/20-295/112-A Date: 01/02/2017</p>

<p>Project Title : Integrating genome scale metabolic analysis of model plant pathogen Ralstonia solanacearum with RNAseq and fluxomics</p>

<p>Essential qualification : M.Tech. in CSE/IT (With specialization in Computational Biology/Bioinformatics) or M.Sc. in Bioinformatics/Biosciences/Molecular Biology Biotechnology preferably with NET/GATE/BET. Candidates should have minimum 55 % mark both in 10th and 10+2 Science examinations and mathematics at 10+2 Science. Desirable: Preference will be given to the candidates having experience in computational analysis of genome sequences or similar projects.</p>

<p>No. of Post : 01</p>

<p>Remuneration : Rs. 25,000/- for the 1st two years and Rs. 28,000/- for the 3rd year for SRF and applicable to the candidate having post graduate degree in Basic Science with NET/GATE/BET qualification or post graduate degree in professional course. Rs. 12,000/- for the 1st two years and Rs. 14,000/- for the 3 rd year for SRF, </p>

<p>Age : 28 years</p>

<p>Duration : Three (03) years or till completion of the project or until further order, whichever is earlier.</p>

<p>Hiring Process : Walk - In<br />Job Role: Research/JRF/SRF</p>

<p>Walk-in-interview will be held on 17th February, 2017, 11.15 a.m. at the office of the Head, Department of Computer Science and Engineering, Tezpur University.</p>

<p>Interested candidates may appear before the interview board with original documents from 10th standard onwards and photocopies of mark sheets, certificates, testimonials, caste certificate (if applicable), experience certificate certificates of NET/GATE/BET or similar examination qualifications, any other testimonials and a copy of recent curriculum vitae (CV) on the day of interview.</p>

<p>More at http://www.tezu.ernet.in/ProjectWalkin/Advt-DoRD-CSE-SSS-20-295-112-A.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/32227/postdoctoral-research-position-in-bioinformatics-in-milan</guid>
  <pubDate>Thu, 20 Apr 2017 12:53:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Research Position in Bioinformatics in Milan]]></title>
  <description><![CDATA[
<p>The lab of Immunobiology of Neurological Disorders has a main interest in the biological processes associated with multiple sclerosis, an inflammatory disorder of the central nervous system. The projects of interest for this application involve research on translational bioinformatics in complex human neurological disorders.</p>

<p>You have a  PhD in Computational Science, Bioinformatics,  or equivalent, and expertise in analysis and modeling of human RNA-seq data, statistics, data mining and machine learning. Excellent communication skills in English (written and oral) is a must. Flexibility and willingness to work across multiple projects and technologies in a rapidly evolving scientific context is required.<br />Salary will depend on qualification and experience. Starting date: immediate.</p>

<p>Interested candidates should send to farina.cinthia@hsr.it:</p>

<p>1. CV (please show evidences of relevant titles, projects, courses, references, etc.)           <br />2. One page with a list of research topics (i.e. ongoing projects)     <br />3. earliest availability</p>

<p>4. 2-3 contact names</p>
]]></description>
</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>
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