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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32129?offset=1440</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41872/autodock-vina-an-open-source-program-for-doing-molecular-docking</guid>
	<pubDate>Sat, 13 Jun 2020 07:55:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41872/autodock-vina-an-open-source-program-for-doing-molecular-docking</link>
	<title><![CDATA[AutoDock Vina: an open-source program for doing molecular docking.]]></title>
	<description><![CDATA[<p><span>AutoDock Vina is an open-source program for doing&nbsp;</span><a href="http://en.wikipedia.org/wiki/Docking_(molecular)">molecular docking</a><span>. It was designed and implemented by&nbsp;</span><a href="http://olegtrott.com/">Dr. Oleg Trott</a><span>&nbsp;in the Molecular Graphics Lab at The Scripps Research Institute.</span>&nbsp;It is especially effective for protein-ligand docking. AutoDock 4 is available under the GNU General Public License. AutoDock is one of the most cited docking software applications in the research community.</p>
<p><img src="http://vina.scripps.edu/img/accuracy.png" width="352" height="264" alt="image" style="border: 0px;"></p>
<p><a href="http://vina.scripps.edu/">http://vina.scripps.edu/</a></p><p>Address of the bookmark: <a href="http://vina.scripps.edu/" rel="nofollow">http://vina.scripps.edu/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/18384/big-genomic-data-on-google-cloud-platform</guid>
	<pubDate>Fri, 17 Oct 2014 02:16:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/18384/big-genomic-data-on-google-cloud-platform</link>
	<title><![CDATA[Big genomic data on Google Cloud Platform]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/ExNxi_X4qug" frameborder="0" allowfullscreen></iframe>As the cost of DNA sequencing has dropped, the volume of data produced has risen into the petabytes. Google is working with the genomics community to define a standard API for working with big genomic data sets in the cloud. Building on Google Cloud Platform, we show how to store, process, explore and share genomic data using technologies like BigQuery, AppEngine MapReduce, R and more.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34445/inc-seq-accurate-single-molecule-reads-using-nanopore-sequencing</guid>
	<pubDate>Mon, 27 Nov 2017 10:38:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34445/inc-seq-accurate-single-molecule-reads-using-nanopore-sequencing</link>
	<title><![CDATA[INC-Seq: accurate single molecule reads using nanopore sequencing]]></title>
	<description><![CDATA[<p><span>INC-Seq reads enabled accurate species-level classification, identification of species at 0.1&nbsp;% abundance and robust quantification of relative abundances, providing a cheap and effective approach for pathogen detection and microbiome profiling on the MinION system.</span></p><p>Address of the bookmark: <a href="https://github.com/CSB5/INC-Seq" rel="nofollow">https://github.com/CSB5/INC-Seq</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18579/cluster-innovation-center-university-of-delhi</guid>
  <pubDate>Wed, 22 Oct 2014 10:39:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[CLUSTER INNOVATION CENTER @ UNIVERSITY OF DELHI]]></title>
  <description><![CDATA[
<p>Applications for Pre-selection of  candidates under ‘Institutions Mode’ for DST-ISPIRE Faculty in  Computational Biology/ Systems Biology/ Bioinformatics</p>

<p>Applications are invited for pre-selection  of candidates for Ministry of Science and Technology, Department of Science and Technology INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE in the area of computational Biology/Systems Biology/Bioinformatics.</p>

<p>Candidates having done their B.Tech/B.E.  and or M.Sc./M.Tech in Computer Science or Biotechnology and Ph.D. in Systems/ Computational Biology or Bioinformatics may apply in the following format prescribed by DST to the Director, Cluster Innovation Center, University Stadium, GC Narang Marg, University of Delhi, Delhi -11107. Detials of other qualification, age limits etc., please visit www.inspire-dst.gov.in.</p>

<p>Application on the prescribed format may be submitted by email to director@cic.du.ac.in before October 25, 2014. Selected candidates shall be called for an interview. The date, time and venue of the interview shall be informed by email/telephone. For more information about Cluster Innovation Center, please visit https://ducic.ac.in.</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35899/reference-free-prediction-of-rearrangement-breakpoint-reads</guid>
	<pubDate>Thu, 08 Mar 2018 05:05:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35899/reference-free-prediction-of-rearrangement-breakpoint-reads</link>
	<title><![CDATA[Reference-free prediction of rearrangement breakpoint reads]]></title>
	<description><![CDATA[<p><span>lideSort-BPR (&nbsp;</span><span>b</span><span>&nbsp;reak&nbsp;</span><span>p</span><span>&nbsp;oint&nbsp;</span><span>r</span><span>&nbsp;eads) is based on a fast algorithm for all-against-all comparisons of short reads and theoretical analyses of the number of neighboring reads. When applied to a dataset with a sequencing depth of 100&times;, it finds &sim;88% of the breakpoints correctly with no false-positive reads. Moreover, evaluation on a real prostate cancer dataset shows that the proposed method predicts more fusion transcripts correctly than previous approaches, and yet produces fewer false-positive reads. To our knowledge, this is the first method to detect breakpoint reads without using a reference genome.</span></p>
<p><span>https://github.com/ewijaya/slidesort-bpr</span></p><p>Address of the bookmark: <a href="https://code.google.com/archive/p/slidesort-bpr/" rel="nofollow">https://code.google.com/archive/p/slidesort-bpr/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19059/ipython-interactive-notebooks</guid>
	<pubDate>Fri, 07 Nov 2014 12:07:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19059/ipython-interactive-notebooks</link>
	<title><![CDATA[IPython: Interactive notebooks]]></title>
	<description><![CDATA[<p>The IPython Notebook is a web-based interactive computational environment where you can combine code execution, text, mathematics, plots and rich media into a single document.</p><p>These notebooks are normal files that can be shared with colleagues, converted to other formats such as HTML or PDF, etc. You can share any publicly available notebook by using the IPython Notebook Viewer service which will render it as a static web page. This makes it easy to give your colleagues a document they can read immediately without having to install anything.</p><p><img src="http://ipython.org/_images/9_home_fperez_prof_grants_1207-sloan-ipython_proposal_fig_ipython-notebook-specgram.png" width="985" height="916" alt="image" style="border: 0px;"><br /><br />To learn more about using the IPython Notebook, you can visit our example collection, and you can read the documentation for all the details on how to use and configure the system. The Notebook Gallery showcases many interesting notebooks covering a variety of topics, from basic programming to advanced scientific computing.</p><p>&nbsp;</p><p>More http://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261</p><p>http://ipython.org/ipython-doc/1/interactive/notebook.html</p><p>Reference http://ipython.org/notebook.html</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36635/circlator-automated-circularization-of-genome-assemblies-using-long-sequencing-reads</guid>
	<pubDate>Tue, 15 May 2018 09:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36635/circlator-automated-circularization-of-genome-assemblies-using-long-sequencing-reads</link>
	<title><![CDATA[Circlator: automated circularization of genome assemblies using long sequencing reads]]></title>
	<description><![CDATA[A tool to circularize genome assemblies. The algorithm and benchmarks are described in the Genome Biology manuscript. 

Citation: "Circlator: automated circularization of genome assemblies using long sequencing reads", Hunt et al, Genome Biology 2015 Dec 29;16(1):294. doi: 10.1186/s13059-015-0849-0. PMID: 26714481.<p>Address of the bookmark: <a href="http://sanger-pathogens.github.io/circlator/" rel="nofollow">http://sanger-pathogens.github.io/circlator/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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