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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/22807?offset=270</link>
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	<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>
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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>
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	<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>
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  <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>
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	<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>
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	<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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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2334/binc-bioinformatics-national-certification-website-address</guid>
	<pubDate>Wed, 14 Aug 2013 09:40:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2334/binc-bioinformatics-national-certification-website-address</link>
	<title><![CDATA[BINC (BioInformatics National Certification) Website address]]></title>
	<description><![CDATA[<p><span>BINC (BioInformatics National Certification) is an initiative of Department of Biotechnology(DBT), Government Of India in coordination with Bioinformatics Center, University of Pune. The objective of the examination is to recognize trained manpower in the area of Bioinformatics. Currently, various Indian universities, Government and private institutions are involved in imparting courses in Bioinformatics in India.</span></p>
<p>Foreign nationals intending to have certification are eligible to appear for BINC examination.<br>Minimum qualification includes a degree from a recognized university/institute in the areas listed in FAQ.<br>Formal training in the area of Bioinformatics is not a prerequisite.<br>Note that the foreign students will only be certified by DBT and are not eligible for the cash award as well as junior research fellowship.</p><p>Address of the bookmark: <a href="http://binc.scisjnu.ernet.in/" rel="nofollow">http://binc.scisjnu.ernet.in/</a></p>]]></description>
	<dc:creator>Kamalakshi Mukherjee</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/2742/baumbach-lab</guid>
  <pubDate>Wed, 21 Aug 2013 10:56:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[Baumbach Lab]]></title>
  <description><![CDATA[
<p>The Computational Biology research group was established in October 2012 at the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark (SDU). It emerged from the Computational Systems Biology group, founded in March 2010 at the Max Planck Institute for Informatics (MPII) and the Cluster of Excellence for Multimodel Computing and Interaction (MMCI) at Saarland University, Saarbrücken, Germany.<br />​<br />The group is headed by Prof. Dr. Jan Baumbach and currently hosts nine PhD students and one postdoctoral fellow at both, IMADA/SDU and MMCI/MPII.</p>

<p>More at &gt;&gt; http://www.baumbachlab.net/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4835/chang-lab</guid>
  <pubDate>Tue, 24 Sep 2013 17:25:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[Chang lab]]></title>
  <description><![CDATA[
<p>The Chang lab is focused on how the activities of hundreds or even thousands of genes (gene parties) are coordinated to achieve biological meaning. We have pioneered methods to predict, dissect, and control large-scale gene regulatory programs; these methods have provided insights into human development, cancer, and aging. A particular interest is how cells know and remember their locations in the body, particularly with the help of long noncoding RNAs.</p>

<p>More at http://changlab.stanford.edu/index.html</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4314/postdocs-positions-in-computer-science-in-helsinki-finland</guid>
  <pubDate>Fri, 06 Sep 2013 10:11:19 -0500</pubDate>
  <link></link>
  <title><![CDATA[PostDocs positions in computer science in HELSINKI, FINLAND]]></title>
  <description><![CDATA[
<p>Several university departments in the Helsinki region, Finland, are looking for postdoctoral researchers in the field of computer science and information technology. Jobs are available at:<br />·       Helsinki Institute for Information Technology HIIT, Aalto University and University of Helsinki, http://www.hiit.fi<br />·       Department of Computer Science, University of Helsinki, http://www.cs.helsinki.fi<br />·       Department of Information and Computer Science, Aalto University, http://ics.aalto.fi<br />·       Department of Computer Science and Engineering, Aalto University, http://cse.aalto.fi<br />·       Department of Mathematics and Statistics, University of Helsinki, http://mathstat.helsinki.fi/english/<br /> <br />Why Helsinki?<br />The collaborating Aalto University and University of Helsinki form a leading hub of computer science and modelling, including Machine learning, Data mining, Algorithms, Computational Logic, Cloud computing, Distributed computing, Human-centric ubiquitous ICT, Bioinformatics, etc.<br />Helsinki region is a safe, pleasant and attractive place to live in, with well-functioning services such as public transport etc. Finland has a comprehensive social security and health care system, including exceptionally good parental leaves, and children's day care services.<br /> <br />Positions are offered in:<br />Algorithm engineering (String Algorithms group)<br />Algorithmic bioinformatics (Genome-Scale Algorithmics group)<br />Automated reasoning and search, especially propositional logic (Computational Logic group)<br />Computational astrophysics and/or data analysis (Computational Methods and Data Analysis for Astrophysics group)<br />Computational biology and statistical methods in bioinformatics (Computational Systems Biology group)<br />Computational creativity and data mining (Discovery group)<br />Dynamic and large-scale networked systems (Data Communications Software group)<br />Intelligent multimodal information access (Content-Based Image and Information Retrieval Group)<br />Machine learning and neuroscience (Statistical Machine Learning group)<br />Machine learning for structured data (Kernel Machines, Pattern Analysis and Computational Biology group)<br />Machine learning methods for infectious disease epidemiology (Bayesian Statistics Group)<br />Probabilistic modeling and machine learning (Complex Systems Computation group)<br />Statistical machine learning (Statistical Machine Learning group)<br />Analysing ubiquitous sensor data (HIIT-Wide Focus Area)<br />Interactive visualization (HIIT-Wide Focus Area)<br />Affective computing and BCI (HIIT-Wide Focus Area)<br />Intelligent user interfaces and/or recommender systems (HIIT-Wide Focus Area)<br />Information retrieval and HCI (HIIT-Wide Focus Area)<br />Machine learning and data analysis, especially information retrieval, HCI, text and context data (HIIT-Wide Focus Area)<br />Probabilistic modeling and data analysis for bioinformatics (HIIT-Wide Focus Area)</p>

<p>More at http://www.hiit.fi/postdoc-call-2013</p>
]]></description>
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