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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41452?offset=380</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5388/biggest-human-brain-project-hbp-launched</guid>
	<pubDate>Mon, 07 Oct 2013 19:50:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5388/biggest-human-brain-project-hbp-launched</link>
	<title><![CDATA[Biggest Human Brain Project (HBP) launched!!!]]></title>
	<description><![CDATA[<p><img src="http://s1.ibtimes.com/sites/www.ibtimes.com/files/styles/v2_article_large/public/2013/10/07/human-brain-project.jpg" width="500" height="500" alt="image" style="border: 0px;"></p><p>"In neuroscience, the project will use neuroinformatics and brain simulation to collect and integrate experimental data, identifying and filling gaps in our knowledge, and prioritising future experiments.</p><p>In medicine, the HBP will use medical informatics to identify biological signatures of brain disease, allowing diagnosis at an early stage, before the disease has done irreversible damage, and enabling personalized treatment, adapted to the needs of individual patients. Better diagnosis, combined with disease and drug simulation, will accelerate the discovery of new treatments, drastically lowering the cost of drug discovery.<br /><br />In computing, new techniques of interactive supercomputing, driven by the needs of brain simulation, will impact a vast range of industries. Devices and systems, modelled after the brain, will overcome fundamental limits on the energy-efficiency, reliability and programmability of current technologies, clearing the road for systems with brain-like intelligence."</p><p>Source:&nbsp;<a href="http://www.forbes.com/sites/jenniferhicks/2013/10/07/the-human-brain-project-begins/">http://www.forbes.com/sites/jenniferhicks/2013/10/07/the-human-brain-project-begins/</a>&nbsp;</p><p>(<a href="https://www.facebook.com/humanbrainproj/info">https://www.facebook.com/humanbrainproj/info</a>)</p><p>Home Page:</p><p><a href="https://www.humanbrainproject.eu/">https://www.humanbrainproject.eu/</a></p><p>Jobs:</p><p><a href="https://www.humanbrainproject.eu/participate/jobs">https://www.humanbrainproject.eu/participate/jobs</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/9586/list-of-bioinformatics-companies-and-genomics-service-providers</guid>
	<pubDate>Wed, 02 Apr 2014 06:52:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/9586/list-of-bioinformatics-companies-and-genomics-service-providers</link>
	<title><![CDATA[List of bioinformatics companies and genomics service providers]]></title>
	<description><![CDATA[<p>Plz check out link for bioinformatics and genomics companies.&nbsp;</p><p>Address of the bookmark: <a href="http://grouthbio.com/Genome_Software_Service.php" rel="nofollow">http://grouthbio.com/Genome_Software_Service.php</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/11107/the-minerva-research-group-for-bioinformatics</guid>
  <pubDate>Tue, 27 May 2014 15:48:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Minerva Research Group for Bioinformatics]]></title>
  <description><![CDATA[
<p>The focus of the bioinformatics group is to use computational approaches to gain an insight into genome evolution in primates.</p>

<p>http://www.eva.mpg.de/genetics/bioinformatics/overview.html?Fsize=0%2C%20%40%2F%27</p>

<p>Kelso Group<br />Department of Evolutionary Genetics<br />Max Planck Institute for Evolutionary Anthropology<br />Deutscher Platz 6<br />04103 Leipzig<br />Germany<br />Phone: +49 341 3550 500</p>

<p>Job: <br />http://www.eva.mpg.de/genetics/bioinformatics/jobs.html?Fsize=0%2C%2B%40</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33976/goldgenomes-online-database</guid>
	<pubDate>Wed, 26 Jul 2017 07:49:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33976/goldgenomes-online-database</link>
	<title><![CDATA[GOLD:Genomes Online Database]]></title>
	<description><![CDATA[<p><span>GOLD</span><span>:Genomes Online Database, is a World Wide Web resource for comprehensive access to information regarding genome and metagenome sequencing projects, and their associated metadata, around the world.</span></p>
<p>https://gold.jgi.doe.gov/</p><p>Address of the bookmark: <a href="https://gold.jgi.doe.gov/" rel="nofollow">https://gold.jgi.doe.gov/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34748/airvf-a-filtering-toolbox-for-precise-variant-calling-in-ion-torrent-sequencing</guid>
	<pubDate>Fri, 22 Dec 2017 00:31:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34748/airvf-a-filtering-toolbox-for-precise-variant-calling-in-ion-torrent-sequencing</link>
	<title><![CDATA[AIRVF: a filtering toolbox for precise variant calling in Ion Torrent sequencing]]></title>
	<description><![CDATA[<p><span>AIRVF that works on flowgram, raw and mapped reads and called variants to reduce artifact-driven false variant calls. Tests on sequencing data of standard reference material showed up to &sim;98% reduction of false variants when combined to conventional public pipelines and &sim;48% to the in-house commercial solution, with a minimal loss of sensitivity</span></p>
<p><span><span>The program with a detailed manual is available at&nbsp;</span><a href="https://sourceforge.net/projects/airvf/" target="">https://sourceforge.net/projects/airvf/</a></span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/airvf/" rel="nofollow">https://sourceforge.net/projects/airvf/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36895/npscarf-real-time-scaffolder-using-spades-contigs-and-nanopore-sequencing-reads</guid>
	<pubDate>Mon, 11 Jun 2018 05:14:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36895/npscarf-real-time-scaffolder-using-spades-contigs-and-nanopore-sequencing-reads</link>
	<title><![CDATA[npScarf: real-time scaffolder using SPAdes contigs and Nanopore sequencing reads]]></title>
	<description><![CDATA[npScarf (jsa.np.npscarf) is a program that connect contigs from a draft genomes to generate sequences that are closer to finish. These pipelines can run on a single laptop for microbial datasets. In real-time mode, it can be integrated with simple structural analyses such as gene ordering, plasmid forming.<p>Address of the bookmark: <a href="http://japsa.readthedocs.io/en/latest/tools/jsa.np.npscarf.html" rel="nofollow">http://japsa.readthedocs.io/en/latest/tools/jsa.np.npscarf.html</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37512/purecn-copy-number-calling-and-snv-classification-using-targeted-short-read-sequencing</guid>
	<pubDate>Thu, 09 Aug 2018 04:09:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37512/purecn-copy-number-calling-and-snv-classification-using-targeted-short-read-sequencing</link>
	<title><![CDATA[PureCN: copy number calling and SNV classification using targeted short read sequencing]]></title>
	<description><![CDATA[<p>This package estimates tumor purity, copy number, and loss of heterozygosity (LOH), and classifies single nucleotide variants (SNVs) by somatic status and clonality. PureCN is designed for targeted short read sequencing data, integrates well with standard somatic variant detection and copy number pipelines, and has support for tumor samples without matching normal samples.</p>
<p>Author: Markus Riester [aut, cre], Angad P. Singh [aut]</p>
<p>Maintainer: Markus Riester &lt;markus.riester at novartis.com&gt;</p>
<div id="bioc_citation_outer">
<p>Citation (from within R, enter&nbsp;<code>citation("PureCN")</code>):</p>
<div id="bioc_citation">
<p>Riester M, Singh A, Brannon A, Yu K, Campbell C, Chiang D, Morrissey M (2016). &ldquo;PureCN: Copy number calling and SNV classification using targeted short read sequencing.&rdquo;&nbsp;<em>Source Code for Biology and Medicine</em>,&nbsp;<strong>11</strong>, 13. doi:&nbsp;<a href="http://doi.org/10.1186/s13029-016-0060-z">10.1186/s13029-016-0060-z</a>.</p>
</div>
</div><p>Address of the bookmark: <a href="http://bioconductor.org/packages/release/bioc/html/PureCN.html" rel="nofollow">http://bioconductor.org/packages/release/bioc/html/PureCN.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</guid>
	<pubDate>Thu, 06 Sep 2018 16:21:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</link>
	<title><![CDATA[LoRMA: A tool for correcting sequencing errors in long reads]]></title>
	<description><![CDATA[<p><span>An error correction method that uses long reads only. The method consists of two phases: first, we use an iterative alignment-free correction method based on de Bruijn graphs with increasing length of&nbsp;</span><em>k</em><span>-mers, and second, the corrected reads are further polished using long-distance dependencies that are found using multiple alignments. According to our experiments, the proposed method is the most accurate one relying on long reads only for read sets with high coverage. Furthermore, when the coverage of the read set is at least 75&times;, the throughput of the new method is at least 20% higher.</span></p>
<blockquote>
<p><span>conda install -c atgc-montpellier lorma</span></p>
</blockquote><p>Address of the bookmark: <a href="https://gite.lirmm.fr/lorma/lorma-releases/wikis/home" rel="nofollow">https://gite.lirmm.fr/lorma/lorma-releases/wikis/home</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</guid>
	<pubDate>Thu, 04 Oct 2018 16:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</link>
	<title><![CDATA[VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules]]></title>
	<description><![CDATA[<p>VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.</p>
<h5>&nbsp;</h5><p>Address of the bookmark: <a href="https://github.com/broadinstitute/VariantBam" rel="nofollow">https://github.com/broadinstitute/VariantBam</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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