<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34711?offset=210</link>
	<atom:link href="https://bioinformaticsonline.com/related/34711?offset=210" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26919/pear-a-fast-and-accurate-illumina-paired-end-read-merger</guid>
	<pubDate>Wed, 06 Apr 2016 13:27:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26919/pear-a-fast-and-accurate-illumina-paired-end-read-merger</link>
	<title><![CDATA[PEAR: a fast and accurate Illumina Paired-End reAd mergeR]]></title>
	<description><![CDATA[<p><strong>PEAR</strong>&nbsp;is an ultrafast, memory-efficient and highly accurate pair-end read merger. It is fully parallelized and can run with as low as just a few kilobytes of memory.</p>
<p>PEAR evaluates all possible paired-end read overlaps and without requiring the target fragment size as input. In addition, it implements a statistical test for minimizing false-positive results. Together with a highly optimized implementation, it can merge millions of paired end reads within a couple of minutes on a standard desktop computer.</p>
<p>More at&nbsp;http://www.exelixis-lab.org/web/software/pear</p>
<p>Paper:&nbsp;http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3933873/</p><p>Address of the bookmark: <a href="http://www.exelixis-lab.org/web/software/pear" rel="nofollow">http://www.exelixis-lab.org/web/software/pear</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36632/tulip-the-uncorrected-long-read-integration-pipeline</guid>
	<pubDate>Tue, 15 May 2018 09:06:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36632/tulip-the-uncorrected-long-read-integration-pipeline</link>
	<title><![CDATA[TULIP - The Uncorrected Long read Integration Pipeline]]></title>
	<description><![CDATA[TULIP currently consists of two Perl scripts, tulipseed.perl and tulipbulb.perl. These are very much intended as prototypes, and additional components and/or implementations are likely to follow.

Tulipseed takes as input alignments files of long reads to sparse short seeds, and outputs a graph and scaffold structures.<p>Address of the bookmark: <a href="https://github.com/Generade-nl/TULIP" rel="nofollow">https://github.com/Generade-nl/TULIP</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42280/urmap-an-ultra-fast-read-mapper</guid>
	<pubDate>Thu, 29 Oct 2020 23:03:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42280/urmap-an-ultra-fast-read-mapper</link>
	<title><![CDATA[URMAP, an ultra-fast read mapper]]></title>
	<description><![CDATA[<p><span>URMAP, a new read mapping algorithm. URMAP is an order of magnitude faster than BWA with comparable accuracy on several validation tests. On a Genome in a Bottle (GIAB) variant calling test with 30&times; coverage 2&times;150 reads, URMAP achieves high accuracy (precision 0.998, sensitivity 0.982 and F-measure 0.990) with the strelka2 caller. However, GIAB reference variants are shown to be biased against repetitive regions which are difficult to map and may therefore pose an unrealistically easy challenge to read mappers and variant callers.</span></p>
<p><span>More at&nbsp;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320720/</span></p><p>Address of the bookmark: <a href="https://github.com/rcedgar/urmap" rel="nofollow">https://github.com/rcedgar/urmap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/933/world-of-omics</guid>
	<pubDate>Tue, 16 Jul 2013 17:11:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/933/world-of-omics</link>
	<title><![CDATA[World of Omics]]></title>
	<description><![CDATA[<p>How many variants of "omics" techniques presently in use ?</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4100/should-you-get-sequenced-not-all-bad-genes-predict-disease</guid>
	<pubDate>Thu, 29 Aug 2013 15:10:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4100/should-you-get-sequenced-not-all-bad-genes-predict-disease</link>
	<title><![CDATA[Should you get sequenced? Not all bad genes predict disease]]></title>
	<description><![CDATA[<p><span>&ldquo;What we really don&rsquo;t know yet is whether the predictive aspects of the genome are going to turn out to be beneficial or potentially harmful&rdquo;</span></p>
<p><span><span>&ldquo;As we roll out genomic medicine we are fighting against this society-wide misconception that having the bad gene means you&rsquo;re going to get the disease. That&rsquo;s only true in a very few cases.&rdquo;</span></span></p>
<p><span><span><strong>Source</strong>:Today Health</span></span></p><p>Address of the bookmark: <a href="http://www.today.com/health/should-you-get-sequenced-not-all-bad-genes-predict-disease-8C11017154" rel="nofollow">http://www.today.com/health/should-you-get-sequenced-not-all-bad-genes-predict-disease-8C11017154</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4183/320000-viruses-in-mammals-yet-to-sequenced-in-future</guid>
	<pubDate>Tue, 03 Sep 2013 08:35:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4183/320000-viruses-in-mammals-yet-to-sequenced-in-future</link>
	<title><![CDATA[320000 viruses in mammals yet to sequenced in future!!!]]></title>
	<description><![CDATA[<p>With current biological technique improvements, finally it is now possible to look at millions of unknown viruses at genomic level and understand the mechanism. According to available data, close to 70 per cent of emerging viral diseases such as HIV/AIDS, West Nile, Ebola, SARS, and influenza, are zoonoses - infections of animals that cross into humans.</p><p>To address the challenges of describing and estimating virodiversity, a team of investigators from Center for Infection and Immunity (CII) and EcoHealth Alliance began in jungles of Bangladesh - home to the flying fox.</p><p>Reference:</p><p><a href="http://economictimes.indiatimes.com/news/news-by-industry/et-cetera/mammals-harbour-at-least-320000-new-viruses/articleshow/22253268.cms">http://economictimes.indiatimes.com/news/news-by-industry/et-cetera/mammals-harbour-at-least-320000-new-viruses/articleshow/22253268.cms</a></p><p><a href="http://www.bbc.co.uk/news/science-environment-23932400">http://www.bbc.co.uk/news/science-environment-23932400</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6130/rna-bioinformatics-and-high-throughput-analysis-jena</guid>
  <pubDate>Sat, 09 Nov 2013 20:03:56 -0600</pubDate>
  <link></link>
  <title><![CDATA[RNA Bioinformatics and High Throughput Analysis Jena]]></title>
  <description><![CDATA[
<p>Research Topics:</p>

<p>High Throughput Sequencing Analysis<br />Comparative Genomics<br />Identification and Annotation of Non-coding RNAs<br />Bioinformatic Analysis and System Biology of Viruses<br />Coevolution of Proteins and RNAs<br />Algorithmic Bioinformatics<br />Phylogenetic Analysis</p>

<p>http://www.rna.uni-jena.de/index.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/10093/bio-rad-acquires-gnubio</guid>
	<pubDate>Sat, 19 Apr 2014 10:36:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/10093/bio-rad-acquires-gnubio</link>
	<title><![CDATA[Bio-Rad Acquires GnuBIO]]></title>
	<description><![CDATA[<p>http://www.businesswire.com/news/home/20140411005331/en/Bio-Rad-Acquires-GnuBIO-Developer-Droplet-Based-DNA-Sequencing#.U1KXnPm1b8o</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/10246/deadly-human-pathogen-cryptococcus-sequenced</guid>
	<pubDate>Fri, 25 Apr 2014 11:02:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/10246/deadly-human-pathogen-cryptococcus-sequenced</link>
	<title><![CDATA[Deadly Human Pathogen Cryptococcus  Sequenced]]></title>
	<description><![CDATA[<p><span>"Now, researchers have sequenced the entire genome and all the RNA products of the most important pathogenic lineage of Cryptococcus neoformans, a strain called H99. The results, which appear in&nbsp;</span><em>PLOS Genetics</em><span>, also describe a number of genetic changes that can occur after laboratory handling of H99 that make it more susceptible to stress, hamper its ability to sexually reproduce and render it less virulent."</span></p><p><span><strong>Source</strong>:</span></p><p><span>http://www.biosciencetechnology.com/news/2014/04/deadly-human-pathogen-cryptococcus-fully-sequenced</span></p><p><span><strong>Paper</strong>:</span></p><p><span>http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1004292</span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/11365/drawback-of-exome-sequencing</guid>
	<pubDate>Mon, 02 Jun 2014 05:46:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/11365/drawback-of-exome-sequencing</link>
	<title><![CDATA[Drawback of Exome Sequencing]]></title>
	<description><![CDATA[<p><span><span>Dr Eric Londin, Assistant Professor, Thomas Jefferson University, USA, stated that analysis of 44 exome datasets from four different testing kits showed that they missed a high proportion of clinically relevant regions in the 56 ACMG genes. "At least one gene in each exome method was missing more than 40 percent of disease-causing genetic variants, and we found that the worst-performing method missed more than 90 percent of such variants in four of the 56 genes," he says.</span><br /></span></p><p><span><strong>Source</strong>:&nbsp;http://www.eurekalert.org/pub_releases/2014-05/esoh-pco052914.php</span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

</channel>
</rss>