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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36191?offset=50</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</guid>
	<pubDate>Thu, 10 Oct 2013 11:53:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</link>
	<title><![CDATA[The anatomy of successful computational biology software]]></title>
	<description><![CDATA[<p>Creators of software widely used in computational biology discuss the factors that contributed to their success</p><p><em>Nature Biotechnology</em><span>&nbsp;spoke with Altschul and several other originators of computational biology software programs widely used today (</span><a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html#t1">Table 1</a><span>). The conversations explored what makes certain software tools successful, the unique challenges of developing them for biological research and how the field of computational biology, as a whole, can move research agendas forward. What follows is an edited compilation of interviews.</span></p><p>Detail @&nbsp;<a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html">http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html</a></p><p>News Source @ Nature</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5748/troyanskaya-lab</guid>
  <pubDate>Fri, 18 Oct 2013 10:57:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Troyanskaya  Lab]]></title>
  <description><![CDATA[
<p>In our research, we combine computational methods with an experimental component in a unified effort to develop comprehensive descriptions of genetic systems of cellular controls, including those whose malfunctioning becomes the basis of genetic disorders, such as cancer, and others whose failure might produce developmental defects in model systems.</p>

<p>Research Interest<br />Genomic Data Integration</p>

<p>Microarray Analysis</p>

<p>Gene and Protein Function Prediction</p>

<p>Detection and Analysis of Chromosomal Abnormalities and Functional Evolution</p>

<p>Integration of Computation and Experiments</p>

<p>Identification of Biological Networks and Pathways</p>

<p>Evaluation and Validation of Computational Predictions</p>

<p>Scalable Visualization-Based Data Analysis</p>

<p>More @ http://reducio.princeton.edu/cm/<br />PI page @ http://reducio.princeton.edu/cm/ogt</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/6380/hidden-markov-models-viterbi-algorithm-markov-chain-exploration-with-script</guid>
	<pubDate>Thu, 14 Nov 2013 13:36:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/6380/hidden-markov-models-viterbi-algorithm-markov-chain-exploration-with-script</link>
	<title><![CDATA[Hidden Markov Models, Viterbi Algorithm, Markov Chain Exploration with script]]></title>
	<description><![CDATA[<p><strong>Hidden Markov Models, the Viterbi Algorithm, and CpG Islands (in VB6)</strong></p><p><strong>Problem :</strong></p><p>The CG island is a stretch of DNA (usually longer than 200 bases) in which the frequency of the CG sequence is higher than other regions. It is also called the CpG island, where "p" simply indicates that "C" and "G" are connected by a phosphodiester bond.<br /><br />CpG islands are often located around the promoters of housekeeping genes (which are essential for general cell functions) or other genes frequently expressed in a cell. At these locations, the CG sequence is not methylated. By contrast, the CG sequences in inactive genes are usually methylated to suppress their expression. The methylated cytosine may be converted to thymine by accidental deamination. Unlike the cytosine to uracil mutation which is efficiently repaired, the cytosine to thymine mutation can be corrected only by the mismatch repair which is very inefficient. Hence, over evolutionary time scales, the methylated CG sequence will be converted to the TG sequence.</p><p>Find step wise explanationand implementation steps at <a href="http://dna.cs.byu.edu/bio465/Labs/hmm.shtml">http://dna.cs.byu.edu/bio465/Labs/hmm.shtml</a></p><p>Source code with explanation <a href="http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/">http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/</a></p><p>Fore detail understanding of HMM read this excellent tutorial <a href="http://www.cs.ubc.ca/~murphyk/Software/HMM/labman2.pdf">http://www.cs.ubc.ca/~murphyk/Software/HMM/labman2.pdf</a></p><p>Viterbi Algo at <a href="http://en.wikipedia.org/wiki/Viterbi_path">http://en.wikipedia.org/wiki/Viterbi_path</a></p><p>For firther reading Wiki page <a href="http://en.wikipedia.org/wiki/Hidden_Markov_model">http://en.wikipedia.org/wiki/Hidden_Markov_model</a></p><p>On CpG island paper and for indepth understanding <a href="http://www.biomedcentral.com/1471-2164/12/S2/S10">http://www.biomedcentral.com/1471-2164/12/S2/S10</a></p><p>&nbsp;</p><p>If you are more interested in exploring&nbsp;Markov Chain Exploration and understand it with graphical version please visit <a href="http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1">http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1</a></p><p>Reference:</p><p>1.<a href="http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1">http://www.planet-source-code.com</a></p><p>2. <a href="http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/">http://www.tannerhelland.com</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6835/roslin-bioinformatics-group</guid>
  <pubDate>Mon, 25 Nov 2013 23:55:25 -0600</pubDate>
  <link></link>
  <title><![CDATA[Roslin Bioinformatics Group]]></title>
  <description><![CDATA[
<p>Roslin Bioinformatics Group</p>

<p>The Law group provides internal Institute-specific development, training and support roles for data manipulation, sequence analysis and any other aspect of the analysis of biological data using computer systems. Additionally we provide databases and applications supporting the international animal science community, particularly tools and resources for genome mapping.</p>

<p>Head: Andy Law. Members: John Bowman (animal facility database applications), Zen Lu (bioinformatics support), Trevor Paterson (software development)</p>

<p>More @ http://www.bioinformatics.ed.ac.uk/groups/roslin-bioinformatics-group</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/7214/lapti-lab</guid>
  <pubDate>Thu, 12 Dec 2013 18:19:12 -0600</pubDate>
  <link></link>
  <title><![CDATA[LAPTI Lab]]></title>
  <description><![CDATA[
<p>The main theme of our research is the understanding of how genetic information is decoded from DNA into RNA and proteins. Someone may find this topic a little strange and argue that we already know how this is happening.</p>

<p>Translational recoding. </p>

<p>RNA editing. </p>

<p>Evolution of the genetic code and translation.</p>

<p>More at http://lapti.ucc.ie/research.html</p>

<p>Lab page http://lapti.ucc.ie/index.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8382/c-dac-launch-supercomputing-facility-param-bio-blaze</guid>
	<pubDate>Tue, 18 Feb 2014 11:55:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8382/c-dac-launch-supercomputing-facility-param-bio-blaze</link>
	<title><![CDATA[C-DAC launch supercomputing facility "Param Bio Blaze" !!!]]></title>
	<description><![CDATA[<p>The bioinformatics centre at Centre for Development of Advanced Computing (C-DAC) completed 10 years, this month. Established in 2004, the centre has been widely used by numerous researchers across the globe and has an ultimate aim of making personalised drugs depending on the composition of a human body.<br /><br />When biological data is processed using computer science, statistics, mathematics and engineering, it constitutes bioinformatics. The technological advancements are bringing new dimensions to the understanding of molecular basis of living organisms. There is immense data generated due to computing, but storage and analysis of this data is becoming a challenge, therefore there is an urgent need of supercomputers.</p><p>The&nbsp;C-DAC will launch Param Bio Blaze, a supercomputing facility, to address the challenges in bioinformatics on Tuesday at a three-day symposium, titled: 'Accelerating biology: Computing life'. The supercomputing facility will be inaugurated on Tuesday by Ramakrishna Ramaswamy, vice-chancellor, Central University of Hyderabad at the Yashada. The new C-DAC's facility will have a capacity of 10 teraflop and will be able to analyse human cells and its functions.</p><p><img src="http://www.datacenterjournal.com/wp-content/uploads/2012/06/supercomputer.jpg" alt="image" width="1024" height="632" style="border: 0px; border: 0px;"></p><p><br />Param Bio Blaze will help have a larger storage space and better computing facility for the bioinformatics sector. The facility will help capture the movement of molecules and also interaction between two molecules and the effects.<br /><br />Applications of Param BioBlaze<br /><br />- Collaboration with National Centre for Cell Science for research on Malaria and understanding how the disease spreads<br /><br />- Collaborative work with Tata Memorial hospital on breast cancer and find out the difference between normal tissues and tissues from breast cancer patients<br /><br />- Designing anti-cancer molecules, a collaborative research with the University of Pune</p><p>Reference:</p><p>Times of India</p><p>Image:datacenterjournal.com</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/fun/view/8509/the-best-bioinformatics-computational-biology-quotes</guid>
	<pubDate>Wed, 26 Feb 2014 17:50:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/fun/view/8509/the-best-bioinformatics-computational-biology-quotes</link>
	<title><![CDATA[The Best Bioinformatics / Computational Biology Quotes]]></title>
	<description><![CDATA[<p><img src="http://bioinformaticsonline.com/mod//photo/hahaha.png" style="border: 0; border: 0px;" alt="image"></p><p>Bioinformatician are not anti-social; We are just genome friendly.</p><p>Bioinformatician would love to change the biological world, but they won't give us the genetic code :P</p><p>If at first you don't succeed; call it version 1.0</p><p>The glass is neither half-full nor half-empty: it's actually have several genomes.</p><p>I'm BioGeek.</p><p>Fedup with LIPS, try God script.</p><p>Idiot, Go ahead, make my data!</p><p>Thank god, my genome just compiled.</p><p>Error message: "Out of space on genome drive:"</p><p>Shut up mobile elements, or i'll flush you out.</p><p>Never underestimate the internet bandwidth, u gotta incomplete.</p><p>Applied fuzzy logic to understand God's logic?</p><p>Warning! Overflow, delete chromosome !</p><p>Be nice to the BioGeek, for all you know they might be the next curator!</p><p>Beware of computational biologist they screw genes and protein.</p><p>Warning! Your genome is full of garbage, delete it !</p><p>Bad or missing mouse genome. Spank the cat? (Y/N)</p><p>Genome make very fast, very accurate mistakes.</p><p>Let's BLAST it.</p><p>Some genome never has transposons. It just develops random features.</p><p>Go watch CINEMA and have BLAST.</p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/8970/j-aires-de-sousa-research-group</guid>
  <pubDate>Wed, 12 Mar 2014 09:57:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[J. Aires de Sousa Research Group]]></title>
  <description><![CDATA[
<p>We are involved in the development of methods and software in chemoinformatics. Current main projects are:</p>

<p>1.automatic learning of chemical reactivity and metabolism,<br />2.simulation of NMR spectra,<br />3.modelling of properties of ionic liquids, and<br />4.representation of molecular chirality.</p>

<p>More at http://joao.airesdesousa.com/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/9204/keep-your-important-ssh-session-running-when-you-disconnect-from-server</guid>
	<pubDate>Sat, 15 Mar 2014 21:39:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/9204/keep-your-important-ssh-session-running-when-you-disconnect-from-server</link>
	<title><![CDATA[Keep Your Important SSH Session Running when You Disconnect from Server !!!]]></title>
	<description><![CDATA[<p>As a Bioinformatician/ Computational biologist we swim in the ocean of genomic/proteomics data, and play with them with an ease. In our day to day simulation, analysis, comparative study we do need to run exhaustive programs, which might take more than a week. In such cases we do need to disconnect from sever in a way that our program/session should not get terminated. To do so there are lots of software, tools such as tmux ( <a href="http://tmux.sourceforge.net/">http://tmux.sourceforge.net/</a>, nohup (<a href="http://ss64.com/bash/nohup.html">http://ss64.com/bash/nohup.html</a>) , byobu (<a href="https://help.ubuntu.com/10.04/serverguide/byobu.html">https://help.ubuntu.com/10.04/serverguide/byobu.html</a>) and other commands (disown -a &amp;&amp; exit), but following are the ones I use the most.</p><p>Screen is like a window manager for your console. It will allow you to keep multiple terminal sessions running and easily switch between them. It also protects you from disconnection, because the screen session doesn&rsquo;t end when you get disconnected.<br /><br />You&rsquo;ll need to make sure that screen is installed on the server you are connecting to. If that server is Ubuntu or Debian, just use this command:<br /><br />sudo apt-get install screen<br /><br />Now you can start a new screen session by just typing screen at the command line. You&rsquo;ll be shown some information about screen. Hit enter, and you&rsquo;ll be at a normal prompt.<br /><br /><strong>To disconnect (but leave the session running)</strong><br /><br />Hit Ctrl + A and then Ctrl + D in immediate succession. You will see the message [detached]<br /><br /><strong>To reconnect to an already running session</strong><br /><br />screen -r<br /><br /><strong>To reconnect to an existing session, or create a new one if none exists</strong><br /><br />screen -D -r<br /><br /><strong>To create a new window inside of a running screen session</strong><br /><br />Hit Ctrl + A and then C in immediate succession. You will see a new prompt.<br /><br /><strong>To switch from one screen window to another</strong><br /><br />Hit Ctrl + A and then Ctrl + A in immediate succession.<br /><br /><strong>To list open screen windows</strong><br /><br />Hit Ctrl + A and then W in immediate succession</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/9341/gerstein-lab</guid>
  <pubDate>Wed, 19 Mar 2014 12:48:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[Gerstein Lab]]></title>
  <description><![CDATA[
<p>The focus of the Gerstein Lab is interpreting personal genomes, particularly in relation to disorders, such as cancer. This endeavor has a number of related aspects described below. Moreover, the approaches we take have broad connections to a variety of data-intensive fields, within the emerging discipline of data science. </p>

<p>Personal Genome Variation: SVs<br />Human Genome Annotation: Processing Next-Gen Sequencing Data<br />Comparative Genomics: Pseudogenes as Molecular Fossils<br />Protein Structure and Function: Macromolecular Motions<br />Analysis of Diverse Networks<br />Genomics at the Forefront of Data Science</p>

<p>Lab page: http://www.gersteinlab.org/</p>
]]></description>
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