<?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/29614?offset=1180</link>
	<atom:link href="https://bioinformaticsonline.com/related/29614?offset=1180" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</guid>
	<pubDate>Tue, 28 Jan 2020 03:21:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</link>
	<title><![CDATA[Kevler: Reference-free variant discovery in large eukaryotic genomes]]></title>
	<description><![CDATA[<p><span>Welcome to&nbsp;</span><span>kevlar</span><span>, software for predicting&nbsp;</span><em>de novo</em><span>&nbsp;genetic variants without mapping reads to a reference genome! kevlar's&nbsp;</span><em>k</em><span>-mer abundance based method calls single nucleotide variants (SNVs), multinucleotide variants (MNVs), insertion/deletion variants (indels), and structural variants (SVs) simultaneously with a single simple model.&nbsp;</span></p>
<p><span>More at&nbsp;<a href="https://kevlar.readthedocs.io/en/latest/">https://kevlar.readthedocs.io/en/latest/</a></span></p>
<p><span><a href="https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf">https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf</a></span></p><p>Address of the bookmark: <a href="https://github.com/kevlar-dev/kevlar" rel="nofollow">https://github.com/kevlar-dev/kevlar</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14800/a-comprehensive-atlas-of-human-gene-activity-released</guid>
	<pubDate>Tue, 02 Sep 2014 14:20:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14800/a-comprehensive-atlas-of-human-gene-activity-released</link>
	<title><![CDATA[A comprehensive atlas of human gene activity released !!!]]></title>
	<description><![CDATA[<div><div id="postDescription_4018558404"><p>A large international consortium of researchers has produced the first comprehensive, detailed map of the way&nbsp;<a href="http://www.hsph.harvard.edu/news/topic/genetics/" target="_blank">genes</a>&nbsp;work across the major cells and tissues of the human body. The findings describe the complex networks that govern gene activity, and the new information could play a crucial role in identifying the genes involved with disease.</p><p><img src="http://www.kurzweilai.net/images/Coexpression-clustering.jpg" alt="image" width="640" height="460" style="border: 0px; border: 0px;"></p><p>We are able to pinpoint the regions of the genome that can be active in a disease and in normal activity, whether it&rsquo;s in a brain cell, the skin, in blood stem cells or in hair follicles. This is a major advance that will greatly increase our ability to understand the causes of disease across the body.</p><p>The research is outlined in a series of papers published March 27, 2014, two in the journal&nbsp;<em>Nature</em>&nbsp;and 16 in other scholarly journals. The work is the result of years of concerted effort among 250 experts from more than 20 countries as part of&nbsp;<a href="http://fantom.gsc.riken.jp/" target="_blank">FANTOM 5 (Functional Annotation of the Mammalian Genome)</a>. The FANTOM project, led by the Japanese institution RIKEN, is aimed at building a complete library of human genes.</p><p>Researchers studied human and mouse cells using a new technology called Cap Analysis of Gene Expression (CAGE), developed at RIKEN, to discover how 95% of all human genes are switched on and off. These &ldquo;switches&rdquo; &mdash; called &ldquo;promoters&rdquo; and &ldquo;enhancers&rdquo; &mdash; are the regions of DNA that manage gene activity. The researchers mapped the activity of 180,000 promoters and 44,000 enhancers across a wide range of human cell types and tissues and, in most cases, found they were linked with specific cell types.</p><p>Referene : www.kurzweilai.net/first-comprehensive-atlas-of-human-gene-activity-released</p></div></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</guid>
	<pubDate>Sat, 02 Jan 2021 07:05:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</link>
	<title><![CDATA[shovill: Assemble bacterial isolate genomes from Illumina paired-end reads]]></title>
	<description><![CDATA[<p><span>Shovill is a pipeline which uses SPAdes at its core, but alters the steps before and after the primary assembly step to get similar results in less time. Shovill also supports other assemblers like SKESA, Velvet and Megahit, so you can take advantage of the pre- and post-processing the Shovill provides with those too.</span></p><p>Address of the bookmark: <a href="https://github.com/tseemann/shovill" rel="nofollow">https://github.com/tseemann/shovill</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/14927/which-of-the-following-programming-language-is-best-for-a-bioinformatics-beginner</guid>
	<pubDate>Thu, 04 Sep 2014 07:51:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/14927/which-of-the-following-programming-language-is-best-for-a-bioinformatics-beginner</link>
	<title><![CDATA[Which of the following programming language is best for a bioinformatics beginner?]]></title>
	<description><![CDATA[<p>I will be doing NGS in the course of my research work and I will like to learn a programming language which is compatible with most bioinformatics tools or software. I basically want to do de-novo assembly, map reads, align reads, and expression analysis. Recommendations welcomed. Which languages would you recommend to a student wishing to enter the world of bioinformatics?</p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</guid>
	<pubDate>Wed, 06 Dec 2017 02:08:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</link>
	<title><![CDATA[COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly]]></title>
	<description><![CDATA[<p><span>An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30&times; simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads.</span></p><p>Address of the bookmark: <a href="ftp://ftp.genomics.org.cn/pub/cope" rel="nofollow">ftp://ftp.genomics.org.cn/pub/cope</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/16160/research-scientist-%E2%80%93-bioinformatics-at-sidra-medical-and-research-center</guid>
  <pubDate>Wed, 10 Sep 2014 14:35:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Scientist – Bioinformatics at Sidra Medical and Research Center]]></title>
  <description><![CDATA[
<p>Sidra Medical and Research Center(Doha, Qatar) is looking for talented Research Scientists (Bioinformatics / NGS Data Analysis).</p>

<p>Research Scientists within the Bioinformatics Program are involved in research related to cutting edge genomics and analysis of omics data. The research will utilize concepts, theories and best practices obtained from bioinformatics discipline and applied to biological and other biomedical data for analysis. The role may also involve designing databases, algorithm and/or computation methods for analyzing genomics and other omics data.  The scientist will be working closely with the Translational Medicine Program within a state-of-the art research setting.</p>

<p>Please check the details of the opening and apply here: http://careers.sidra.org/sidra/Vacan...acancyID=60181</p>
]]></description>
</item>
<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>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/16472/internship-nipgr</guid>
  <pubDate>Sat, 13 Sep 2014 16:02:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[INTERNSHIP @ NIPGR]]></title>
  <description><![CDATA[
<p>Applications are invited from suitable candidates for six months ‘Training Fellowship' at National Institute of Plant Genome Research (NIPGR).</p>

<p>About National Institute Of Plant Genome Research (NIPGR) http://www.nipgr.res.in/</p>

<p>The National Institute of Plant Genome Research is an autonomous institution supported by the Department of Biotechnology, Government of India. It is committed to make the institute a premier Institution for plant genomic research in the country. It was established to contribute in the achievement of such hopes as a part of national effort for meeting the challenges in the midst of fast pace of international genomic research and grasping of opportunities on long-term basis.</p>

<p>About the Internship:</p>

<p>The selected intern(s) will work in the area of in Bioinformatics under the BTISNET program of DBT in the Distributed Information Sub center (DISC) facility at NIPGR, New Delhi, under the supervision of Dr. Gitanjali Yadav, Scientist, NIPGR.</p>

<p>Who can apply:</p>

<p>Students currently pursuing the final year of Masters Degree (or equivalent) in Bioinformatics/Biotechnology with strong interest in Computational Biology and First class/division throughout academic career may apply.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</guid>
	<pubDate>Fri, 11 May 2018 05:07:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[MECAT: fast mapping, error correction, and de novo assembly for single-molecule sequencing reads]]></title>
	<description><![CDATA[<p>MECAT is an ultra-fast Mapping, Error Correction and de novo Assembly Tools for single molecula sequencing (SMRT) reads. MECAT employs novel alignment and error correction algorithms that are much more efficient than the state of art of aligners and error correction tools. MECAT can be used for effectively de novo assemblying large genomes. For example, on a 32-thread computer with 2.0 GHz CPU , MECAT takes 9.5 days to assemble a human genome based on 54x SMRT data, which is 40 times faster than the current&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>. MECAT performance were compared with&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>,&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>&nbsp;and&nbsp;<a href="http://canu.readthedocs.io/en/latest/">Canu(v1.3)</a>&nbsp;in five real datasets. The quality of assembled contigs produced by MECAT is the same or better than that of the&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>&nbsp;and&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>.&nbsp;</p>
<p>https://www.nature.com/articles/nmeth.4432</p><p>Address of the bookmark: <a href="https://github.com/xiaochuanle/MECAT" rel="nofollow">https://github.com/xiaochuanle/MECAT</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/16682/java-utilities-for-next-generation-sequencing-by-pierre-lindenbaum</guid>
	<pubDate>Mon, 15 Sep 2014 17:24:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/16682/java-utilities-for-next-generation-sequencing-by-pierre-lindenbaum</link>
	<title><![CDATA[Java utilities for Next Generation Sequencing  by Pierre Lindenbaum]]></title>
	<description><![CDATA[<div>
<div>
<p>Java utilities for Bioinformatics</p>
</div>
<div>
<p><a href="https://github.com/lindenb/jvarkit">https://github.com/lindenb/jvarkit</a></p>
</div>
</div><p>Address of the bookmark: <a href="https://github.com/lindenb/jvarkit" rel="nofollow">https://github.com/lindenb/jvarkit</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>

</channel>
</rss>