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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26972?offset=390</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/31251/bioinformatics-opening-at-icgeb-new-delhi</guid>
  <pubDate>Thu, 02 Mar 2017 04:16:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics opening at ICGEB NEW DELHI]]></title>
  <description><![CDATA[
<p>ICGEB NEW DELHI</p>

<p>Applications are invited for:</p>

<p>Junior Research Fellow, in a DBT funded project, is available in Translational Health Group, ICGEB, New Delhi</p>

<p>Qualifications:</p>

<p>Education: M.Sc. (preferably in Biotechnology, Life Sciences or Zoology, Chemistry, Bioinformatics). Candidates with hands on experience on GC-MS data acquisition and analysis will be given preference. Bioinformatics expertise required.</p>

<p>Fellowship: As per DBT guidelines.</p>

<p>Tenure: The position is purely on temporary basis with an initial tenure of six months and based on satisfactory performance may continue until the completion of the project.</p>

<p>Closing date for applications: 04/03/2017</p>

<p>Please send a "TWO PAGE" CV by email to:  th.icgeb@gmail.com on or before the last date.</p>

<p>Research Associate, in a DBT funded project, is available in Translational Health Group, ICGEB, New Delhi</p>

<p>Qualifications:</p>

<p>Education: Ph.D. (in Biology, Biotechnology, Chemistry, Bioinformatics). Candidates with hands on experience on GC-MS data acquisition and analysis will be given preference. </p>

<p>Fellowship: As per DBT guidelines.</p>

<p>Tenure: The position is purely on temporary basis with an initial tenure of six months and  based on satisfactory performance may continue until the completion of the project.</p>

<p>Closing date for applications: 04/03/2017</p>

<p>Please send a "TWO PAGE" CV by email to: th.icgeb@gmail.com on or before the last date.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31526/sequenceserver</guid>
	<pubDate>Fri, 10 Mar 2017 08:51:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31526/sequenceserver</link>
	<title><![CDATA[sequenceserver]]></title>
	<description><![CDATA[<p><span>SequenceServer lets you rapidly set up a BLAST+ server with an intuitive user interface for use locally or over the web.</span></p>
<p><span><span>More at&nbsp;</span><a href="http://sequenceserver.com/">http://sequenceserver.com</a><span>.</span></span></p><p>Address of the bookmark: <a href="https://github.com/wurmlab/sequenceserver" rel="nofollow">https://github.com/wurmlab/sequenceserver</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32018/tmap-torrent-mapping-alignment-program-general-notes</guid>
	<pubDate>Sun, 02 Apr 2017 15:53:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32018/tmap-torrent-mapping-alignment-program-general-notes</link>
	<title><![CDATA[TMAP - torrent mapping alignment program General Notes]]></title>
	<description><![CDATA[<p>TMAP - torrent mapping alignment program <a href="https://github.com/iontorrent/TS/tree/master/Analysis/TMAP#general-notes"></a>General Notes</p>
<p>TMAP is a fast and accurate alignment software for short and long nucleotide sequences produced by next-generation sequencing technologies.</p>
<ul>
<li>
<p>The latest TMAP is unsupported. To use a supported version, please see the TMAP version associated with a Torrent Suite release below.</p>
</li>
<li>
<p>Get the latest source code:</p>
<div>
<pre>git clone git://github.com/iontorrent/TMAP.git
 <span>cd</span> TMAP
 git submodule init
 git submodule update</pre>
</div>
</li>
</ul>
<p>https://github.com/iontorrent/TS/tree/master/Analysis/TMAP</p><p>Address of the bookmark: <a href="https://github.com/iontorrent/TS/tree/master/Analysis/TMAP" rel="nofollow">https://github.com/iontorrent/TS/tree/master/Analysis/TMAP</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32134/lifemap</guid>
	<pubDate>Mon, 10 Apr 2017 05:42:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32134/lifemap</link>
	<title><![CDATA[Lifemap]]></title>
	<description><![CDATA[<p><strong>Lifemap</strong> is an interactive tool to explore the WHOLE NCBI TAXONOMY. The concept used in <strong>Lifemap</strong> is similar to the one used in cartography with tools like Google Maps&copy; or Open Street Maps: exploring is done by zooming and panning.</p>
<div>
<p>&nbsp;The current tree contains ALL species present in NCBI taxonomy as of <span style="text-decoration: underline;">October 18th, 2016</span>: 1,135,169 species including 10,545 Archaea, 418,777 Bacteria and 705,847 Eukaryotes. The Lifemap tree is updated every two weeks.</p>
</div>
<p>&nbsp;All the nodes in the tree are clickable. This displays various information and options:</p>
<ul>
<li>The species name (and the associated common name if there is one)</li>
<li>The rank (kingdom, family, class, species...)</li>
<li>Ability to go to the corresponding node/species on NCBI web site (displayed in a new window)</li>
<li>Possibility to download the corresponding subtree in newick extended format</li>
<li>Possibilty to get the whole lineage from the current node/tip to the root of the tree.</li>
</ul><p>Address of the bookmark: <a href="http://lifemap-ncbi.univ-lyon1.fr/" rel="nofollow">http://lifemap-ncbi.univ-lyon1.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32187/chromhmm-chromatin-state-discovery-and-characterization</guid>
	<pubDate>Wed, 19 Apr 2017 04:06:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32187/chromhmm-chromatin-state-discovery-and-characterization</link>
	<title><![CDATA[ChromHMM: Chromatin state discovery and characterization]]></title>
	<description><![CDATA[<p><span>ChromHMM is software for learning and characterizing chromatin states. ChromHMM can integrate multiple chromatin datasets such as ChIP-seq data of various histone modifications to discover de novo the major re-occuring combinatorial and spatial patterns of marks. ChromHMM is based on a multivariate Hidden Markov Model that explicitly models the presence or absence of each chromatin mark. The resulting model can then be used to systematically annotate a genome in one or more cell types. By automatically computing state enrichments for large-scale functional and annotation datasets ChromHMM facilitates the biological characterization of each state. ChromHMM also produces files with genome-wide maps of chromatin state annotations that can be directly visualized in a genome browser.&nbsp;</span><br><br></p>
<ul>
<li><a href="http://compbio.mit.edu/ChromHMM/ChromHMM.zip">ChromHMM software v1.12</a>&nbsp;(<a href="http://compbio.mit.edu/ChromHMM/versionlog.txt">version log</a>)</li>
<li><a href="http://compbio.mit.edu/ChromHMM/ChromHMM_manual.pdf">ChromHMM manual</a></li>
</ul><p>Address of the bookmark: <a href="http://compbio.mit.edu/ChromHMM/" rel="nofollow">http://compbio.mit.edu/ChromHMM/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32379/enrichr-a-comprehensive-gene-set-enrichment-analysis</guid>
	<pubDate>Thu, 27 Apr 2017 05:42:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32379/enrichr-a-comprehensive-gene-set-enrichment-analysis</link>
	<title><![CDATA[Enrichr: a comprehensive gene set enrichment analysis]]></title>
	<description><![CDATA[<p><span>Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at:&nbsp;</span><a href="http://amp.pharm.mssm.edu/Enrichr" target="">http://amp.pharm.mssm.edu/Enrichr</a><span>.</span></p>
<p>https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkw377</p><p>Address of the bookmark: <a href="http://amp.pharm.mssm.edu/Enrichr/" rel="nofollow">http://amp.pharm.mssm.edu/Enrichr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32905/bigmac-breaking-inaccurate-genomes-and-merging-assembled-contigs-for-long-read-metagenomic-assembly</guid>
	<pubDate>Mon, 22 May 2017 05:43:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32905/bigmac-breaking-inaccurate-genomes-and-merging-assembled-contigs-for-long-read-metagenomic-assembly</link>
	<title><![CDATA[BIGMAC : breaking inaccurate genomes and merging assembled contigs for long read metagenomic assembly]]></title>
	<description><![CDATA[<p>This tool is for users to upgrade their metagenomics assemblies using long reads. This includes fixing mis-assemblies and scaffolding/gap-filling. If you encounter any issues, please contact me at&nbsp;<a href="mailto:kklam@eecs.berkeley.edu">kklam@eecs.berkeley.edu</a>. My name is Ka-Kit Lam.</p>
<p>https://github.com/kakitone/MetaFinisherSC</p>
<p>https://github.com/kakitone/BIGMAC</p><p>Address of the bookmark: <a href="https://github.com/kakitone/BIGMAC" rel="nofollow">https://github.com/kakitone/BIGMAC</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34475/oxford-nanopore-sequencing-hybrid-error-correction-and-de-novo-assembly-of-a-eukaryotic-genome</guid>
	<pubDate>Wed, 29 Nov 2017 05:08:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34475/oxford-nanopore-sequencing-hybrid-error-correction-and-de-novo-assembly-of-a-eukaryotic-genome</link>
	<title><![CDATA[Oxford Nanopore Sequencing, Hybrid Error Correction, and de novo Assembly of a Eukaryotic Genome]]></title>
	<description><![CDATA[<p><span>Monitoring the progress of DNA molecules through a membrane pore has been postulated as a method for sequencing DNA for several decades. Recently, a nanopore-based sequencing instrument, the Oxford Nanopore MinION, has become available that we used for sequencing the S. cerevisiae genome. To make use of these data, we developed a novel open-source hybrid error correction algorithm Nanocorr (</span><a href="https://github.com/jgurtowski/nanocorr">https://github.com/jgurtowski/nanocorr</a><span>) specifically for Oxford Nanopore reads, as existing packages were incapable of assembling the long read lengths (5-50kbp) at such high error rate (between ~5 and 40% error). With this new method we were able to perform a hybrid error correction of the nanopore reads using complementary MiSeq data and produce a de novo assembly that is highly contiguous and accurate: the contig N50 length is more than ten-times greater than an Illumina-only assembly (678kb versus 59.9kbp), and has greater than 99.88% consensus identity when compared to the reference. Furthermore, the assembly with the long nanopore reads presents a much more complete representation of the features of the genome and correctly assembles gene cassettes, rRNAs, transposable elements, and other genomic features that were almost entirely absent in the Illumina-only assembly.</span></p><p>Address of the bookmark: <a href="http://schatzlab.cshl.edu/data/nanocorr/" rel="nofollow">http://schatzlab.cshl.edu/data/nanocorr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/32629/bienko-and-crosetto-labs</guid>
  <pubDate>Fri, 12 May 2017 07:42:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bienko and Crosetto Labs]]></title>
  <description><![CDATA[
<p>We are two groups of scientists doing frontier research in quantitative biology and biomedicine. The Bienko group is interested in exploring the fundamental design principles controlling how DNA is packed in the eukaryotic nucleus and its relation to gene expression regulation. The Crosetto group engineers new molecular methods for single-cell and spatially resolved omic measurements of DNA, RNA, and proteins, with a strong focus on tumor heterogeneity. By sharing ideas and resources, we work synergistically towards a more quantitative understanding of life’s processes in healthy and diseased conditions.</p>

<p>https://bienkocrosettolabs.org/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/32822/phd-positions-in-genova-at-dibris-univ-of-genoa-italy</guid>
  <pubDate>Thu, 18 May 2017 00:04:07 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD positions in Genova at DIBRIS - Univ. of Genoa, Italy]]></title>
  <description><![CDATA[
<p>PhD positions in Genova at DIBRIS - Univ. of Genoa (Italy)</p>

<p>http://www.disi.unige.it/person/MasulliF/ricerca/PhDinGenova2017.html</p>

<p>The call for some funded positions for  the 3 years PhD studies  at the Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS) in Genova is available at</p>

<p>http://www.studenti.unige.it/postlaurea/dottorati/XXXIII/ENG/</p>

<p>The deadline for applications is June13, 2017 and the PhD courses and fellowships should start on Nov 2017.</p>

<p>Details for the application to the  PhD Program in Computer Science and Systems Engineering (CODICE 6608) are at http://phd.dibris.unige.it/csse/index.php/how-to-apply</p>

<p>The research activity of my research group is focused on Computational Intelligence, Machine Learning, Bioinformatics, Systems Biology, and Positive Technology as described at http://www.disi.unige.it/person/MasulliF/ricerca/index.html</p>

<p>The research themes proposed by me and Prof. Stefano Rovetta are:</p>

<p>- Computational Intelligence and Machine Learning (see http://www.disi.unige.it/person/MasulliF/ricerca/Phd2017-T1.html)</p>

<p>- Computational Intelligence and Health and Wellbeing Support( see http://www.disi.unige.it/person/MasulliF/ricerca/Phd2017-T3.html)</p>

<p>You can also propose a different research theme belonging to the research activity of my group.</p>

<p>Looking for self-motivated PhD candidates, interested to the mathematical aspects of their research and to the development of new algorithms for intelligent data analysis, and skilled in programming and   in  thorough experimental data analysis. They will be part of my research group and will collaborate to our research projects and publications.</p>

<p>Italian and international students interested to work are invited  to send their cv  and the name/email-addresses of 3 referees to my email address francesco.masulli@unige.it A.S.A.P.</p>
]]></description>
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