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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26378?offset=700</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/851/the-institute-for-molecular-bioscience-imb-bailey-lab</guid>
  <pubDate>Sun, 14 Jul 2013 11:53:08 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Institute for Molecular Bioscience (IMB), Bailey Lab]]></title>
  <description><![CDATA[
<p>Pattern recognition and computational biology</p>

<p>MEME Suite software development; gene expression; mathematical modelling; gene regulation and transcription</p>

<p>Specialization:<br />Pattern recognition and modelling in computational biology</p>

<p>Link @ http://www.imb.uq.edu.au/tim-bailey</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</guid>
	<pubDate>Wed, 19 Apr 2017 10:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</link>
	<title><![CDATA[DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies]]></title>
	<description><![CDATA[<p>DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies</p>
<p>Our work is published in Scientific Reports:</p>
<p>Ye, C. et al. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Sci. Rep. 6, 31900; doi: 10.1038/srep31900 (2016).</p>
<p><a href="http://www.nature.com/articles/srep31900">http://www.nature.com/articles/srep31900</a></p>
<p>The manual can be downloaded from:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx">https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx</a></p>
<p>To use precompiled versions,please go to:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/tree/master/compiled">https://github.com/yechengxi/DBG2OLC/tree/master/compiled</a></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/yechengxi/DBG2OLC" rel="nofollow">https://github.com/yechengxi/DBG2OLC</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/858/the-centre-for-bioinformatics-biomarker-discovery-and-information-based-medicine-cibm</guid>
  <pubDate>Sun, 14 Jul 2013 12:31:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine (CIBM)]]></title>
  <description><![CDATA[
<p>The Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine (CIBM) is committed to shortening the process of obtaining novel discoveries to achieve distinctively better outcomes in clinical practice and translational individualised medicine.</p>

<p>Link @ http://www.newcastle.edu.au/research-and-innovation/centre/cibm/about-us</p>
]]></description>
</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/pages/view/900/bioruby-ruby-packages-for-biologist</guid>
	<pubDate>Mon, 15 Jul 2013 01:36:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/900/bioruby-ruby-packages-for-biologist</link>
	<title><![CDATA[BioRuby :Ruby packages for biologist]]></title>
	<description><![CDATA[<p>BioRuby is a package of Open Source Ruby code, with classes for DNA and protein sequence analysis, alignment, database parsing, and other Bioinformatics tools.<br />BioRuby project provides an integrated environment in bioinformatics for the Ruby language. This project is supported by University of Tokyo (Human Genome Center), Kyoto University(Bioinformatics Center) and the Open Bio Foundation. The project was supported by Information-technology Promotion Agency (IPA) as an Exploratory Software Project in 2005<br />RubyForge is a home for open source Ruby projects: RubyForge is a home for open source Ruby projects. BioRuby project was started in late 2000, and is still in progress. Currently, there are over 80 files and 15,000 lines (except comment-only lines) in our source code. This might be equivalent to twice or more lines of other languages because of Ruby's extremely high descriptive power.</p><p>Classes for <br />Multiple alignment (Bio::Alignment), <br />Gene Ontology(Bio::GO), <br />PDB (Bio::PDB), <br />FANTOM database(Bio::FANTOM), <br />GFF (Bio::GFF) and KEGG<br />Orthology (Bio::KEGG::KO).</p><p>They also added support for many applications such as PSORT, SOSUI, TargetP, TMHMM, GenScan, ClustalW, MAFFT, and KEGG API.</p><p>Wiki Links<br />http://bioruby.open-bio.org/wiki/BioRubyOnRails<br />http://dev.bioruby.org/en/</p><p>BioRuby in Anger<br />http://dev.bioruby.org/en/?BioRuby+in+Anger</p><p>BioRuby RDocs<br />http://bioruby.org/rdoc/</p><p>BioRuby Tutorial Website<br />http://dev.bioruby.org/en/?Tutorial.rd</p><p>Why BioRuby Hub for BioRuby<br />http://www.linuxjournal.com/article/5915</p><p>Social Coding Hub for BioRuby<br />http://www.linuxjournal.com/article/5915</p><p>Bioinformatics on Rails: BioRuby Tutorial<br />http://bioinforuby.blogspot.com/2008/02/bioruby-tutorial.html</p><p>RRA BioRuby<br />http://raa.ruby-lang.org/project/bioruby/</p><p>BioRuby Project Discussion Group<br />http://portal.open-bio.org/mailman/listinfo/bioruby</p><p>BioRuby related Projects: Project tree<br />http://rubyforge.org/softwaremap/trove_list.php?form_cat=252</p><p>Reference<br />http://www.jsbi.org/journal/GIW03/GIW03P191.pdf</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32481/sspace</guid>
	<pubDate>Fri, 05 May 2017 05:42:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32481/sspace</link>
	<title><![CDATA[SSPACE]]></title>
	<description><![CDATA[<p>SSPACE standard is a stand-alone program for scaffolding pre-assembled contigs using NGS paired-read data. It is unique in offering the possibility to manually control the scaffolding process. By using the distance information of paired-end and/or matepair data, SSPACE is able to assess the order, distance and orientation of your contigs and combine them into scaffolds. Currently we offer this as a command-line tool in Perl. The input data is given by pre-assembled contig sequences (FASTA) and NGS paired-read data (Illumina/454/Solid FASTA or FASTQ). The final scaffolds are provided in FASTA format.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE" rel="nofollow">https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/871/postdoctoral-position-in-bioinformatics-sweden</guid>
  <pubDate>Sun, 14 Jul 2013 13:49:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral position in bioinformatics @ Sweden]]></title>
  <description><![CDATA[
<p>Information about the department<br />The Department of Mathematical Sciences at Chalmers University of Technology and the University of Gothenburg has about 170 faculty and staff and is the largest department of mathematical sciences in the Nordic countries. The department belongs to both Chalmers University of Technology and the University of Gothenburg (for more information see http://www.chalmers.se/math/).</p>

<p>Job description<br />We are looking for a motivated, self-driven post-doctoral researcher to work with large-scale sequence data analysis. The position is for 24 months and located at Mathematical Statistics, Department of Mathematical Sciences in Erik Kristiansson’s research group. We are focused on methods development for and analysis of next generation DNA sequencing, in particular comparative metagenomics and gene expression analysis (RNA-seq). We have strong interdisciplinary profile and are actively collaborating with several experimental groups, especially within the environmental sciences, ecology, infectious diseases and cancer genomics. More information is available at http://bioinformatics.math.chalmers.se.</p>

<p>The Post-doctoral position is an appointment that offers an opportunity to qualify for further research positions within academia or industry. The majority of your working time is devoted to your own research, normally as a member of a research group. Included in your work is also to take part in supervision of Ph.D. students and M.Sc thesis students. Teaching of undergraduate students may also be included to a small extent.</p>

<p>The employment is limited to a maximum of 2 years (1+1).</p>

<p>Qualifications<br />The applicant should have Ph.D. degree preferably in bioinformatics, mathematics, statistics, computer science or equivalent by the start of the appointment. Experience from analysis of large-scale data, in particular from next generation DNA sequencing, is highly valued. The applicant should also be proficient in programming (e.g. Python/Java/C) and comfortable with Unix/Linux systems. Interaction with experimental biologists is central and good collaborative skills are therefore important. Fluency in written and spoken English is a strong requirement. As a post-doctoral researcher you are expected to work independently and to be able to supervise/co-supervise PhD and Master’s students.</p>

<p>Application procedure<br />The application should be marked with Ref 20130126 and written in English. The application should be sent electronically via Chalmers webpage.</p>

<p>Application deadline: September 8, 2013.</p>

<p>For questions, please contact: <br />Ass prof. Erik Kristiansson, Matematiska Vetenskaper, erik.kristiansson@chalmers.se, +46 31-772 3521, +46 70-5259751.</p>

<p>Chalmers continuously strive to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.</p>
]]></description>
</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/6420/studentship-and-traineeship-university-of-madras</guid>
  <pubDate>Sat, 16 Nov 2013 19:27:40 -0600</pubDate>
  <link></link>
  <title><![CDATA[STUDENTSHIP and TRAINEESHIP @ University of Madras]]></title>
  <description><![CDATA[
<p>Bioinformatics Infrastructure Facility<br />University of Madras<br />Chennai 600 025</p>

<p>Applications are invited for the STUDENTSHIP and TRAINEESHIP vacancies to carry out project/research work in the DBT - Bioinformatics Infrastructure Facility with consolidated stipend of Rs.5,000/- per month.</p>

<p>Essential Qualification</p>

<p>Student Trainee: Those who have completed M.Sc., Bioinformatics/Biophysics/Life sciences or Pursuing M.Tech., Bioinformatics/Biotechnology</p>

<p>Duration : 3-4 Months</p>

<p>Student Trainee: Those who are pursuing M.Sc Bioinformatics/Biophysics/ Life sciences/others</p>

<p>Duration : 2-3 Months</p>

<p>Mail your CV on or before 25th November 2013 to shirai2011@gmail.com and hard copy to "Dr. D. Velmurugan, Professor &amp; Head, CAS in Crystallography and Biophysics, University of Madras, Guindy Campus, Chennai 600 025". Also, the applicants are requested to attend the interview on 29th November, 2013 at 11 A.M.</p>

<p>Advertisement:</p>

<p>www.unom.ac.in/uploads/announcements/bifadvertisement_20131114080003_23240.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/32713/salzberg-lab</guid>
  <pubDate>Mon, 15 May 2017 05:14:01 -0500</pubDate>
  <link></link>
  <title><![CDATA[Salzberg lab]]></title>
  <description><![CDATA[
<p>We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.</p>

<p>https://salzberg-lab.org/</p>
]]></description>
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