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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/4183?offset=610</link>
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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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/5350/introduction-of-epigenomics</guid>
	<pubDate>Sun, 06 Oct 2013 04:59:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/5350/introduction-of-epigenomics</link>
	<title><![CDATA[Introduction of Epigenomics]]></title>
	<description><![CDATA[<ul>
<li><a href="http://www.genome.gov/27532724#al-1">What is the epigenome?</a></li>
<li><a href="http://www.genome.gov/27532724#al-2">What does the epigenome do?</a></li>
<li><a href="http://www.genome.gov/27532724#al-3">What makes up the epigenome?</a></li>
<li><a href="http://www.genome.gov/27532724#al-4">Is the epigenome inherited?</a></li>
<li><a href="http://www.genome.gov/27532724#al-5">What is imprinting?</a></li>
<li><a href="http://www.genome.gov/27532724#al-6">Can the epigenome change?</a></li>
<li><a href="http://www.genome.gov/27532724#al-7">What makes the epigenome change?</a></li>
<li><a href="http://www.genome.gov/27532724#al-8">How do changes in the epigenome contribute to cancer?</a></li>
<li><a href="http://www.genome.gov/27532724#al-9">How are researchers exploring the epigenome?</a></li>
</ul><p>Address of the bookmark: <a href="http://www.genome.gov/27532724" rel="nofollow">http://www.genome.gov/27532724</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/6302/a-allele-of-slc24a5-gene-is-found-to-be-responsible-for-variation-in-skin-color-of-south-east-asians-and-europeans</guid>
	<pubDate>Tue, 12 Nov 2013 21:02:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/6302/a-allele-of-slc24a5-gene-is-found-to-be-responsible-for-variation-in-skin-color-of-south-east-asians-and-europeans</link>
	<title><![CDATA[A-allele of SLC24A5 gene is found to be responsible for variation in skin color of South-East Asians and Europeans]]></title>
	<description><![CDATA[<p><strong>Key finding</strong>:</p><ol>
<li><span>rs1426654 SNP of <em>SLC24A5</em>&nbsp;gene is decider of skin pigmentation variation in South Asia</span></li>
<li><span><span>rs1426654-A allele is widely spread throughout the Indian subcontinent&nbsp;</span></span></li>
<li><span>Skin pigmentation is also account by the combination of processes like selection and demographic history of populations affected by their language and origin</span></li>
<li><span><span>Sign of positive selection in Europeans, Middle East, Pakistan, Central Asia and North India but not in South India</span></span></li>
<li><span><span>In European , A-allele is almost reached to fixation</span></span></li>
</ol><p><span><span><strong>Paper</strong>:</span></span></p><p><span><span><a href="http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1003912">http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1003912</a></span></span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/10379/your-stressdepression-came-from-ancestor</guid>
	<pubDate>Sun, 04 May 2014 18:46:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/10379/your-stressdepression-came-from-ancestor</link>
	<title><![CDATA[Your stress/depression came from ancestor]]></title>
	<description><![CDATA[<p>"A study published in&nbsp;<em>Nature Neuroscience</em>&nbsp;finds that stress in early life alters the production of small RNAs, called microRNAs, in the sperm of mice. The mice show depressive behaviours that persist in their progeny."</p><p>Source:</p><p>http://www.nature.com/news/sperm-rna-carries-marks-of-trauma-1.15049</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33826/geneprof-analysis-of-high-throughput-sequencing-experiment</guid>
	<pubDate>Wed, 05 Jul 2017 16:47:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33826/geneprof-analysis-of-high-throughput-sequencing-experiment</link>
	<title><![CDATA[GeneProf: analysis of high-throughput sequencing experiment]]></title>
	<description><![CDATA[<div>GeneProf is a web-based, graphical software suite that allows users to analyse data produced using high-throughput sequencing platforms (RNA-seq and ChIP-seq; "Next-Generation Sequencing" or NGS): Next-gen analysis for next-gen data!</div>
<p>Some of GeneProf's highlights include:</p>
<ul>
<li><strong>Easy-to-use web-based interface:</strong>Access your data at any time from any computer with a working internet connection -- no need to install software! (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_introduction.jsp#section:SystemRequirements">Section 'System Requirements'</a>).</li>
<li><strong>Analysis wizards make your life easy:</strong>Step-by-step workflows make it easy to analyse high-throughput data within a minimum of hands-on time. (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_conceptsexplained.jsp#subconcept:AnalysisWizards">SubConcept 'Analysis Wizards'</a>).</li>
<li><strong>Versatile modules:</strong>Advanced users and data analysis experts benefit from GeneProf's broad range of analysis modules, which can be combined freely into sophisticated workflows (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_conceptsexplained.jsp#concept:Workflows">Concept 'Workflows'</a>).</li>
<li><strong>Integrated Analysis:</strong>Analysis of&nbsp;<em>ChIP-seq</em>&nbsp;and&nbsp;<em>RNA-seq</em>&nbsp;data in one place, plus support for the integration of other external data (e.g. from microarrays).</li>
<li><strong>Comprehensive Resource:</strong>GeneProf provides a comprehensive resource of&nbsp;<em>fully analyzed</em>&nbsp;next-generation sequencing data. Experimental results can be easily accessed and compared and the analysis procedures employed to produce the data are fully transparent (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_tutorials.jsp#tutorial:ExaminingPublicNext-GenDatausingGeneProf">Tutorial 'Examining Public Next-Gen Data..'</a>).</li>
<li><strong>Extensibility:</strong>Algorithm developers and computer programmers can develop their own modules and extend GeneProf. Existing software can be easily wrapped in the workflow framework (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_advancedtopics.jsp#section:ModuleDevelopment:AddingnewFunctionalitytoGeneProf">Section 'Module Development: Adding new..'</a>) and data from GeneProf may be used externally (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_advancedtopics.jsp#section:WebAPI:RetrievingDatafromGeneProf">Section 'Web API: Retrieving Data from ..'</a>).</li>
</ul>
<p>&nbsp;</p>
<p>GeneProf is academic software developed at the&nbsp;<a href="http://www.crm.ed.ac.uk/">Centre for Regenerative Medicine</a>&nbsp;/&nbsp;<a href="http://www.crm.ed.ac.uk/about/institute-stem-cell-research">Institute for Stem Cell Research</a>,&nbsp;<a href="http://www.ed.ac.uk/">University of Edinburgh</a>&nbsp;and has benefited from funding by the&nbsp;<a href="http://www.mrc.ac.uk/">Medical Research Council</a>&nbsp;and the&nbsp;<a href="http://www.eurosystemproject.eu/">EU Framework 7 Project "EuroSyStem"</a>.</p><p>Address of the bookmark: <a href="https://www.geneprof.org/GeneProf/index.jsp" rel="nofollow">https://www.geneprof.org/GeneProf/index.jsp</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology</guid>
	<pubDate>Tue, 19 Dec 2017 18:49:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology</link>
	<title><![CDATA[1mb long DNA with Nanopore technology]]></title>
	<description><![CDATA[<p>The first continuous DNA read of more than a million bases (&gt;1Mb) has been achieved, using Oxford Nanopore sequencing technology. Congratulations to Martin Smith and collaborators! Read more: http://bit.ly/2j5TNCO</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36476/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</guid>
	<pubDate>Fri, 04 May 2018 19:16:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36476/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]></title>
	<description><![CDATA[<p><span>Flye is a de novo assembler for long and noisy reads, such as those produced by PacBio and Oxford Nanopore Technologies. The algorithm uses an A-Bruijn graph to find the overlaps between reads and does not require them to be error-corrected. After the initial assembly, Flye performs an extra repeat classification and analysis step to improve the structural accuracy of the resulting sequence. The package also includes a polisher module, which produces the final assembly of high nucleotide-level quality.</span></p><p>Address of the bookmark: <a href="https://github.com/fenderglass/Flye" rel="nofollow">https://github.com/fenderglass/Flye</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36806/manta-rapid-detection-of-structural-variants-and-indels-for-germline-and-cancer-sequencing-applications</guid>
	<pubDate>Mon, 28 May 2018 09:41:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36806/manta-rapid-detection-of-structural-variants-and-indels-for-germline-and-cancer-sequencing-applications</link>
	<title><![CDATA[Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications.]]></title>
	<description><![CDATA[Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for analysis of germline variation in small sets of individuals and somatic variation in tumor/normal sample pairs. Manta discovers, assembles and scores large-scale SVs, medium-sized indels and large insertions within a single efficient workflow.<p>Address of the bookmark: <a href="https://github.com/Illumina/manta" rel="nofollow">https://github.com/Illumina/manta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37496/gsearch-a-fast-and-flexible-general-search-tool-for-whole-genome-sequencing</guid>
	<pubDate>Mon, 06 Aug 2018 17:19:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37496/gsearch-a-fast-and-flexible-general-search-tool-for-whole-genome-sequencing</link>
	<title><![CDATA[gSearch: a fast and flexible general search tool for whole-genome sequencing]]></title>
	<description><![CDATA[<p><span>gSearch compares sequence variants in the Genome Variation Format (GVF) or Variant Call Format (VCF) with a pre-compiled annotation or with variants in other genomes. Its search algorithms are subsequently optimized and implemented in a multi-threaded manner.&nbsp;</span></p><p>Address of the bookmark: <a href="http://ml.ssu.ac.kr/gSearch/index.html" rel="nofollow">http://ml.ssu.ac.kr/gSearch/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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