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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/22807?offset=370</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32076/ngs-teaching-material</guid>
	<pubDate>Wed, 05 Apr 2017 04:29:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32076/ngs-teaching-material</link>
	<title><![CDATA[NGS teaching material]]></title>
	<description><![CDATA[<p><span>High throughput sequencing (HTS) technologies are being applied to a wide range of important topics in biology. However, the analyses of non-model organisms, for which little previous sequence information is available, pose specific problems. This course addresses the specific strengths and weaknesses of alternative HTS technologies, the computational resources needed for HTS, and how to analyze non-model species using HTS. The course consists of a practical training module, HTS bioinformatics training, and lecturing/seminars of HTS approaches specifically targeting non-model organisms.</span></p><p>Address of the bookmark: <a href="http://marinetics.org/teaching/hts/Assembly.html" rel="nofollow">http://marinetics.org/teaching/hts/Assembly.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<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/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/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/bookmarks/view/32709/cabog-celera-assembler-with-best-overlap-graph</guid>
	<pubDate>Mon, 15 May 2017 05:04:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32709/cabog-celera-assembler-with-best-overlap-graph</link>
	<title><![CDATA[CABOG: Celera Assembler with Best Overlap Graph]]></title>
	<description><![CDATA[<p>CABOG (Celera Assembler with Best Overlap Graph) is scientific software for&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/24/24/2818.abstract">DNA research</a>. CABOG has been a critical component of many genome sequencing projects. CABOG operates on small genomes such as bacterial as well as large genomes such as mammalian. CABOG is an extension of the Celera Assembler software that was originally developed at&nbsp;<a href="http://www.celera.com/">Celera</a>&nbsp;for the 2001 publication of the first draft human genome sequence. The software was released to the public domain in 2004. Its open source&nbsp;<a href="http://wgs-assembler.sf.net/">repository</a>&nbsp;on Source Forge is an internet resource for scientists around the world.&nbsp;</p>
<p>CABOG is one of many software programs called genome assemblers. These programs exist to overcome the fundamental limitation of all sequencing machines, namely, that they read out very few DNA letters at a time. These programs reconstruct genomes that are billions of letters long from the hundreds of letters per read that modern sequencers provide. What these programs do is often described as a scaled up version of a family solving a jigsaw puzzle.</p>
<p>The CABOG software was the first to accomplish many scientific goals. It was the first to assemble the genome of a multicellular organism (<em>Drosophila melanogaster</em>, 2000). It was the first to assemble both parental haplotypes of one human genome (J. Craig Venter, 2007). It was the first to assemble environmental sequence from the oceans (Sargasso Sea in 2004 and Global Ocean Sampling in 2007). It was first to combine reads from first-generation Sanger sequencing machines and second-generation pyrosequencing machines (Marine microbes, 2006). Today, CABOG is one of the leading assembly programs for data sets that include paired end data from the Roche 454 line of sequencing machines.</p><p>Address of the bookmark: <a href="http://www.jcvi.org/cms/research/projects/cabog/overview/" rel="nofollow">http://www.jcvi.org/cms/research/projects/cabog/overview/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32726/ergo-20-bioinformatics-suites</guid>
	<pubDate>Tue, 16 May 2017 08:14:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32726/ergo-20-bioinformatics-suites</link>
	<title><![CDATA[ERGO 2.0 Bioinformatics suites]]></title>
	<description><![CDATA[<p>ERGO 2.0 provides a systems biology informatics toolkit centered on comparative genomics to capture, query, and visualize sequenced genomes. &nbsp;Using Igenbio's proprietary algorithms, and the most comprehensive genomic database integrated with the largest collection of microbial metabolic and non-metabolic pathways, ERGO&trade; assigns functions to genes, integrates genes into pathways, and identifies previously unknown or mischaracterized genes, cryptic pathways, and gene products.&nbsp;</p><p>Address of the bookmark: <a href="https://www.igenbio.com/ergo/" rel="nofollow">https://www.igenbio.com/ergo/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/1469/prime-minister%E2%80%99s-100k-genome-project</guid>
	<pubDate>Thu, 08 Aug 2013 09:40:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/1469/prime-minister%E2%80%99s-100k-genome-project</link>
	<title><![CDATA[Prime Minister’s 100k Genome Project]]></title>
	<description><![CDATA[<p>Genomics Ebgland is destined to sequence 100,000 patients over the next five year in England.&nbsp; A landmark project by british government.</p><p>Genomics England will play a key role in building on the UK&rsquo;s long track record as leader in medical science advances to push the boundaries by unlocking the power of DNA data. The UK will become the first ever country to introduce this technology in its mainstream health system &ndash; leading the global race for better tests, better drugs and above all better, more personalised care.</p><p>http://www.genomicsengland.co.uk/100k-genome-project/</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/1720/postdoctoral-associate-bioinformatics-at-duke-university-medical-center</guid>
  <pubDate>Sat, 10 Aug 2013 18:38:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Associate - Bioinformatics  at Duke University Medical Center]]></title>
  <description><![CDATA[
<p>The Department of Biostatistics and Bioinformatics at Duke University Medical Center is seeking a Postdoctoral Associate for a one year appointment to work on several high-dimensional research projects. The specific goals of the project are to identify genes or molecular markers that are predictive of clinical outcomes in renal and prostate cancer.</p>

<p>Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.</p>

<p>This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.</p>

<p>For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.</p>

<p>For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf</p>

<p>Duke University is an Equal Opportunity/Affirmative Action Employer.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/view/2021</guid>
	<pubDate>Mon, 12 Aug 2013 09:27:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/2021</link>
	<title><![CDATA[What are the difference between BioRuby and BioGem?]]></title>
	<description><![CDATA[<p>I came across two diferent but matching term BioRuby and BioGem. What are the difference between these two term? If both are using same Ruby language for development then why did they develope two different biological packages.</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4090/computational-biology-in-the-21st-century-making-sense-out-of-massive-data</guid>
	<pubDate>Thu, 29 Aug 2013 08:32:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4090/computational-biology-in-the-21st-century-making-sense-out-of-massive-data</link>
	<title><![CDATA[Computational Biology in the 21st Century: Making Sense out of Massive Data]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/I99UiA_vaJQ" frameborder="0" allowfullscreen></iframe>Computational Biology in the 21st Century: Making Sense out of Massive Data    
    
Air date:  Wednesday, February 01, 2012, 3:00:00 PM
Category:  Wednesday Afternoon Lectures  
 
Description:  The last two decades have seen an exponential increase in genomic and biomedical data, which will soon outstrip advances in computing power to perform current methods of analysis. Extracting new science from these massive datasets will require not only faster computers; it will require smarter algorithms. We show how ideas from cutting-edge algorithms, including spectral graph theory and modern data structures, can be used to attack challenges in sequencing, medical genomics and biological networks. 

The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. 

Author:  Dr. Bonnie Berger  
Runtime:  00:58:06  
Permanent link:  http://videocast.nih.gov/launch.asp?17563]]></description>
	
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