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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/9400?offset=130</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23167/graphmap-a-highly-sensitive-and-accurate-mapper-for-long-error-prone-reads</guid>
	<pubDate>Mon, 06 Jul 2015 08:46:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23167/graphmap-a-highly-sensitive-and-accurate-mapper-for-long-error-prone-reads</link>
	<title><![CDATA[GraphMap - A highly sensitive and accurate mapper for long, error-prone reads]]></title>
	<description><![CDATA[<p>GraphMap is a novel mapper targeted at aligning long, error-prone third-generation sequencing data.<br>It is&nbsp;<strong>designed to handle Oxford Nanopore MinION 1d and 2d reads</strong>&nbsp;with very high sensitivity and accuracy, and also presents a significant improvement over the state-of-the-art for PacBio read mappers.</p>
<p>GraphMap was also designed for ease-of-use: the&nbsp;<strong>default parameters</strong>&nbsp;can handle a wide range of read lengths and error profiles, including:&nbsp;<em>Illumina</em>,&nbsp;<em>PacBio</em>&nbsp;and&nbsp;<em>Oxford Nanopore</em>.<br>This is an especially important feature for technologies where the error rates and error profiles can vary widely across, or even within, sequencing runs.</p>
<p><a href="http://biorxiv.org/content/early/2015/06/10/020719">http://biorxiv.org/content/early/2015/06/10/020719</a></p><p>Address of the bookmark: <a href="https://github.com/isovic/graphmap" rel="nofollow">https://github.com/isovic/graphmap</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27841/covcal-coverage-read-count-calculator</guid>
	<pubDate>Wed, 15 Jun 2016 18:08:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27841/covcal-coverage-read-count-calculator</link>
	<title><![CDATA[CovCal: Coverage / Read Count Calculator]]></title>
	<description><![CDATA[<h2>Coverage / Read Count Calculator</h2>
<h4>Calculate how much sequencing you need to hit a target depth of coverage (or vice versa).</h4>
<p><span>Instructions:</span> set the read length/configuration and genome size, then select what you want to calculate.</p>
<p>Written by <a href="http://stephenturner.us/" target="blank">Stephen Turner</a>, based on the <a href="http://www.ncbi.nlm.nih.gov/pubmed/3294162" target="_blank">Lander-Waterman formula</a>, inspired by <a href="http://core-genomics.blogspot.com/2016/05/how-many-reads-to-sequence-genome.html" target="_blank">a similar calculator</a> written by James Hadfield. Coverage is calculated as <em>C=LN/G</em> and reads as <em>N=CG/L</em> where <em>C</em> = Coverage (X),<em>L</em> = Read length (bp), <em>G</em> = Haploid genome size (bp), and <em>N</em> = Number of reads. Source code <a href="https://github.com/stephenturner/covcalc" target="_blank">on GitHub</a>.</p><p>Address of the bookmark: <a href="http://apps.bioconnector.virginia.edu/covcalc/" rel="nofollow">http://apps.bioconnector.virginia.edu/covcalc/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</guid>
	<pubDate>Tue, 23 May 2017 05:28:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</link>
	<title><![CDATA[SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology]]></title>
	<description><![CDATA[<p><span>SIMBA</span><span>, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS) platforms quickly, easily and effectively. SIMBA also is open source tool, i.e., can be freely downloaded, shared and modified.</span></p>
<p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1344-7</p><p>Address of the bookmark: <a href="http://ufmg-simba.sourceforge.net/" rel="nofollow">http://ufmg-simba.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34515/metasim-a-sequencing-simulator-for-genomics-and-metagenomics</guid>
	<pubDate>Mon, 04 Dec 2017 07:18:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34515/metasim-a-sequencing-simulator-for-genomics-and-metagenomics</link>
	<title><![CDATA[MetaSim A Sequencing Simulator for Genomics and Metagenomics.]]></title>
	<description><![CDATA[<p><span>Our software can be used to&nbsp;</span><strong>generate collections of synthetic reads</strong><span>&nbsp;that reflect the diverse taxonomical composition of typical metagenome data sets. Based on a database of given genomes, the program allows the user to&nbsp;</span><strong>design a metagenome</strong><span>&nbsp;by specifying the number of genomes present at different levels of the NCBI taxonomy, and then to collect reads from the metagenome using a&nbsp;</span><strong>simulation of a number of different sequencing technologies</strong><span>. A population sampler optionally produces evolved sequences based on source genomes and a given evolutionary tree.&nbsp;</span></p><p>Address of the bookmark: <a href="http://ab.inf.uni-tuebingen.de/software/metasim/" rel="nofollow">http://ab.inf.uni-tuebingen.de/software/metasim/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40707/vt-a-variant-tool-set-that-discovers-short-variants-from-next-generation-sequencing-data</guid>
	<pubDate>Tue, 28 Jan 2020 03:44:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40707/vt-a-variant-tool-set-that-discovers-short-variants-from-next-generation-sequencing-data</link>
	<title><![CDATA[vt: a variant tool set that discovers short variants from Next Generation Sequencing data.]]></title>
	<description><![CDATA[<p><span>vt is a variant tool set that discovers short variants from Next Generation Sequencing data.</span></p>
<p><span><a href="https://genome.sph.umich.edu/wiki/Vt">https://genome.sph.umich.edu/wiki/Vt</a></span></p>
<p><a href="https://github.com/atks/vt">https://github.com/atks/vt</a></p><p>Address of the bookmark: <a href="https://genome.sph.umich.edu/wiki/Vt" rel="nofollow">https://genome.sph.umich.edu/wiki/Vt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43892/choosing-the-right-ngs-sequencing-instrument-for-your-study</guid>
	<pubDate>Wed, 15 Jun 2022 00:37:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43892/choosing-the-right-ngs-sequencing-instrument-for-your-study</link>
	<title><![CDATA[Choosing the Right NGS Sequencing Instrument for Your Study]]></title>
	<description><![CDATA[<p>The right sequencing instrument for your study depends on your project goal. Setting aside turnaround time and price, it essentially comes down to the numbers of reads and read length you need for your experiment. Below, we've described and compared metrics for each of the instruments available. If you&rsquo;re new to high-throughput sequencing and have questions about how you should design your sequencing run, fill out our&nbsp;<a href="https://genohub.com/ngs-consultation/"><span>free consultation form</span></a>&nbsp;and we'll get in touch with you to help.</p>
<p>More at&nbsp;https://genohub.com/ngs-instrument-guide/</p><p>Address of the bookmark: <a href="https://genohub.com/ngs-instrument-guide/" rel="nofollow">https://genohub.com/ngs-instrument-guide/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4210/uni-computing-bergen-norway</guid>
  <pubDate>Tue, 03 Sep 2013 18:40:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Uni Computing Bergen Norway]]></title>
  <description><![CDATA[
<p>Info on Uni Computing (Webpage: http://www.bccs.uni.no/) :</p>

<p>Uni Computing (formerly Uni BCCS) is a department of Uni Research, affiliated with the University of Bergen.</p>

<p>5 groups in this lab works on computational resources, methods, algorithms, and software.</p>

<p>Following two bioinformatics groups are:</p>

<p>The Computational Biology Unit (CBU) provides education and research in bioinformatics focused on functional genomics.</p>

<p>The Computational Ecology Unit (CEU) is basically deal with population fluctuations, behavioural patterns and the ways life cycles emerge.</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2631/what-junk-dna-it%E2%80%99s-an-operating-system</guid>
	<pubDate>Mon, 19 Aug 2013 15:24:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2631/what-junk-dna-it%E2%80%99s-an-operating-system</link>
	<title><![CDATA[What Junk DNA? It’s an Operating System]]></title>
	<description><![CDATA[<p>The report adds to growing experimental support for the idea that all that extra stuff in the human genes, once referred to as &ldquo;junk DNA,&rdquo; is more than functionless, space-filling material that happens to make up nearly 98% of the genome. The paper adds to a growing body of knowledge establishing a considerable role for this material in the regulation of gene expression and its potential role in human disease.</p><p>Address of the bookmark: <a href="http://www.genengnews.com/keywordsandtools/print/3/32115/" rel="nofollow">http://www.genengnews.com/keywordsandtools/print/3/32115/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/2991/illumina-reveals-first-dataset-of-long-reads</guid>
	<pubDate>Fri, 23 Aug 2013 06:29:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/2991/illumina-reveals-first-dataset-of-long-reads</link>
	<title><![CDATA[Illumina reveals first dataset of long reads]]></title>
	<description><![CDATA[<p>With the help of Moleculo technology , acquired by Illumina releases new service for long reads sequencing i.e., &nbsp;<a href="http://www.illumina.com/services/long-read-sequencing-service.ilmn">FastTrack Long Reads</a>.</p><p>Average read length is around<span>&nbsp;8,500 base pairs in release dataset.</span>&nbsp;Best thing about this, there is not much effect on cost and quality of data.</p><p>You can also check following pages for publications on long reads and more:</p><p><a href="http://www.illumina.com/services/long-read-sequencing-service.ilmn">http://www.illumina.com/services/long-read-sequencing-service.ilmn</a></p><p><a href="http://blog.basespace.illumina.com/2013/07/22/first-data-set-from-fasttrack-long-reads-early-access-service/">http://blog.basespace.illumina.com/2013/07/22/first-data-set-from-fasttrack-long-reads-early-access-service/</a></p><p>&nbsp;</p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4212/eivind-hovigs-lab</guid>
  <pubDate>Tue, 03 Sep 2013 19:06:29 -0500</pubDate>
  <link></link>
  <title><![CDATA[Eivind Hovig's Lab]]></title>
  <description><![CDATA[
<p>Bioinformatics relevant research topics are:</p>

<p>genomic scale studies<br />endogenous mechanisms of mutations, germ line and somatic <br />computational aspects of immunology in cancer <br />signalling networks<br />three-dimensional organization of information in the nucleus<br />gene silencing<br />metastatic cross-talk<br />kinase signaling<br />personalized medicine<br />detection of biomarkers in cancer <br />historical DNA variation</p>

<p>From : http://www.ous-research.no/hovig/</p>

<p>Group address:<br />Eivind Hovig, The Norwegian Radium Hospital, Montebello, 0310 Oslo,Norway<br />Email: ehovig@radium.uio.no</p>
]]></description>
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