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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/11355?offset=550</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</guid>
	<pubDate>Wed, 15 Mar 2017 14:31:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</link>
	<title><![CDATA[Software and Tools to detect structure variation with long reads !!]]></title>
	<description><![CDATA[<p>Uncovering the connection between genetics and heritable diseases requires an approach that looks at all the variant bases and types in a genome. While a PacBio&nbsp;<em>de novo</em>&nbsp;assembly resolves the most novel SV variants. 8-10X PacBio coverage of single genomes or trios reveals triple the SVs detectable by short-read data.</p><p>With&nbsp;<span style="text-decoration: underline;"><a href="http://www.pacb.com/smrt-science/">Single Molecule, Real-Time (SMRT) Sequencing</a></span>, you can access structural variations having a broad range of sizes, types, and GC content with the ability to:</p><ul>
<li>Uncover missing heritability linked to structural variation</li>
<li>Unambiguously identify genomic context and variant breakpoints at the sequence level to unravel the genetic etiology of disease</li>
<li>Resolve structural variation across the complete size spectrum with basepair resolution</li>
</ul><p>Following are the SV tools, which can assist you to achieve your goal.</p><p><strong>Sniffles:</strong>&nbsp;Structural variation caller using third generation sequencing</p><p>Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter) or NGM-LR with the optional SAM attributes enabled!&nbsp;</p><p>More at&nbsp;https://github.com/fritzsedlazeck/Sniffles</p><p><strong style="font-size: 12.8px;"><br />MultiBreak-SV:</strong> It identifies structural variants from next-generation paired end data, third-generation long read data, or data from a combination of sequencing platforms.</p><p>There are two pieces of software in this release: (1) a pre-processor that takes machineformat (.m5) BLASR files, and (2) MultiBreak-SV. For installation and usage instructions, see doc/MultiBreakSV-Manual.txt.</p><p>More at&nbsp;https://github.com/raphael-group/multibreak-sv</p><p><strong style="font-size: 12.8px;"><br />Parliament:</strong>&nbsp;A Structural Variation Tool. Why ask a single sv-detection approach to find every variant when you can have a parliament of tools deciding?</p><p>Publication about the algorithm and &ldquo;&hellip;the first long-read characterization of structural variation in a diploid human personal genome&hellip;&rdquo; (HS1011) -&nbsp;<a href="http://www.biomedcentral.com/1471-2164/16/286">&ldquo;Assessing structural variation in a personal genome&mdash;towards a human reference diploid genome&rdquo;</a></p><p>More at&nbsp;https://sourceforge.net/projects/parliamentsv/</p><p>https://www.dnanexus.com/papers/Parliament_Info_Sheet.pdf</p><p><br /><strong>PBHoney:</strong>&nbsp;the structural variation discovery tool&nbsp;<br /><br />PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</p><p>Read The Paper&nbsp;<a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a></p><p>More at&nbsp;https://sourceforge.net/projects/pb-jelly/</p><p><strong><br />SMRT-SV:</strong> Structural variant and indel caller for PacBio reads</p><p>Structural variant (SV) and indel caller for PacBio reads based on methods from&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>.</p><p>SMRT-SV provides an official software package for tools described in&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>&nbsp;and adds several key features including the following.</p><ul>
<li>Unified variant calling user interface with built-in cluster compute support</li>
<li>Small indel calling (2-49 bp)</li>
<li>Improved inversion calling (<code>screenInversions</code>)</li>
<li>Quality metric for SV calls based on number of local assemblies supporting each call</li>
<li>Higher sensitivity for SV calls using tiled local assemblies across the entire genome instead of "signature" regions</li>
<li>Genotyping of SVs with Illumina paired-end reads from WGS samples</li>
</ul><p>More at&nbsp;https://github.com/EichlerLab/pacbio_variant_caller</p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/843/structural-polymorphism-analysis-from-ngs-data</guid>
  <pubDate>Sat, 13 Jul 2013 17:12:47 -0500</pubDate>
  <link></link>
  <title><![CDATA[Structural polymorphism analysis from NGS data]]></title>
  <description><![CDATA[
<p>The LabEx BASC (Biodiversity, Agroecosystems, Society, Climate), a network of 13 laboratories of the Paris-Saclay Scientific Cluster, is seeking a bioinformatician to analyze Next Generation Sequencing (NGS) data analysis. In the context of a flagship project aiming at understanding and improving the adaptive capacity of agroecosystems it will be critical to establish a link between sequence variation, functional variation, gene/protein expression and phenotypic adaptation.</p>

<p>The successful candidate will be in charge of the detection of polymorphisms including structural variants, of the comparison of multiple and diverse genomes of a same species and of the construction of pan- and core-genomes. These challenging tasks will require bioinformatics developments and implementation of methods for accommodating the high level of repetitiveness of complex genomes. The tools will be integrated into pipelines and made available to end-users through the Galaxy platform. The bioinformatician will therefore also have to provide researchers with advices on their experimental designs in order to ensure compliance of produced datasets with pipelines requirements. He/she will be hosted by a bioinformatics/informatics team (7 people) (http://moulon.inra.fr/index.php/fr/equipestransversales/atelier-de-bioinformatique) which has computational facilities and expertise in NGS data analysis, and will benefit as well from national and international collaborative networks (Aplibio http://www.renabi.fr/platforms/aplibio/, Transplant http://transplantdb.eu, AMAIZING http://www.amaizing.fr/).</p>

<p>The position requires a doctoral degree (PhD) in bioinformatics with strong expertise in script writing (Python/Perl) and pipeline development. </p>

<p>Applicants should send a CV and the names of 2 referees willing to provide a letter of recommendation to joets@moulon.inra.fr.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32011/fools-guide</guid>
	<pubDate>Sun, 02 Apr 2017 14:31:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32011/fools-guide</link>
	<title><![CDATA[Fools guide]]></title>
	<description><![CDATA[<p><span>This website and accompaning documents are intended as a tool to help researchers dealing with non-model organisms acquire and process transcriptomic high-throughput sequencing data without having to learn extensive bioinformatics skills. It covers all steps from tissue collection, sample preparation and computer setup, through addressing biological questions with gene expression and SNP data.</span></p>
<p>http://sfg.stanford.edu/denovo.html</p>
<p>http://sfg.stanford.edu/sequencing.html</p>
<p>http://sfg.stanford.edu/BLAST.html</p>
<p>http://sfg.stanford.edu/denovo.html&nbsp;</p><p>Address of the bookmark: <a href="http://sfg.stanford.edu/guide.html" rel="nofollow">http://sfg.stanford.edu/guide.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/914/welch-lab</guid>
  <pubDate>Mon, 15 Jul 2013 18:21:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Welch Lab]]></title>
  <description><![CDATA[
<p>They are based in the Department of Genetics at the University of Cambridge. </p>

<p>The research covers diverse areas of evolutionary biology, and molecular evolution in particular. It combines theoretical and empirical approaches, and particularly evolutionary inference from genome sequence data.</p>

<p>Links @ http://www.gen.cam.ac.uk/research/welch/GroupPage/Home.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32399/mapping-ngs</guid>
	<pubDate>Tue, 02 May 2017 07:58:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32399/mapping-ngs</link>
	<title><![CDATA[Mapping NGS]]></title>
	<description><![CDATA[<p>NGS data are just a bunch of sequences, you have no idea which region in the genome each sequences comes from, which gene it represents...<br>To know that you have to align the sequences to the reference sequence. The reference sequence is in most cases the full genome sequence but sometimes, a library of EST sequences is used.<br>In either way, aligning your sequence reads to the reference sequence is called mapping.</p>
<p>The most used mappers of DNA-seq data are&nbsp;<a href="http://bio-bwa.sourceforge.net/" target="_blank">BWA</a>&nbsp;and&nbsp;<a href="http://bowtie-bio.sourceforge.net/bowtie2/index.shtml" target="_blank">Bowtie</a>&nbsp;for DNA-Seq data and&nbsp;<a href="http://tophat.cbcb.umd.edu/" target="_blank">Tophat</a>,&nbsp;<a href="https://github.com/alexdobin/STAR" target="_blank">STAR</a>&nbsp;or&nbsp;<a href="http://www.ccb.jhu.edu/software/hisat/index.shtml" target="_blank">HISAT</a>&nbsp;for RNA-Seq data. Mappers differ in which options they can take in, how fast and how accurate they are. Bowtie is faster than BWA, but looses some sensitivity (does not map an equal amount of reads to the correct position in the genome).</p><p>Address of the bookmark: <a href="http://wiki.bits.vib.be/index.php/Mapping_of_NGS_data" rel="nofollow">http://wiki.bits.vib.be/index.php/Mapping_of_NGS_data</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/1212/computational-proteomics-lets-remember-the-basics</guid>
	<pubDate>Thu, 01 Aug 2013 17:24:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/1212/computational-proteomics-lets-remember-the-basics</link>
	<title><![CDATA[Computational Proteomics : Lets remember the basics]]></title>
	<description><![CDATA[<p>I spend some of my valuable time in computational drug designing sector. I remember my initial proteomics days, playing with interactive protein visualization software and dreaming big. Fortunately or unfortunately, I switched to genomics and handling the genomic floods in Petabytes which is expected to be in Brontobytes in coming years. Did I mention Brontobytes ??? Let me call to my server personnel &hellip; it gonna tsunami !!!!!</p><p>Today, refreshing my old memories I decided to blog about the basic knowledge of biochemistry and computational proteomics&nbsp;skills, but after I found several article on internet saying exactly what I had wanted to say I thought I might as well just redirect BOL's blog readers there instead:</p><p>Here is the list of website and videos links which provide a good resource for you basic chemistry need:</p><p><a href="http://tecreativ.blogspot.co.uk/2012/09/funny-shortcut-remember-periodic-table.html"></a><a href="http://tecreativ.blogspot.co.uk/2012/09/funny-shortcut-remember-periodic-table.html"></a><a href="http://tecreativ.blogspot.co.uk/2012/09/funny-shortcut-remember-periodic-table.html"></a><a href="http://tecreativ.blogspot.co.uk/2012/09/funny-shortcut-remember-periodic-table.html">http://tecreativ.blogspot.co.uk/2012/09/funny-shortcut-remember-periodic-table.html</a></p><p>This blog have some specific hindi word to remember entire periodic table. I really like</p><p>Group 14 (C Si Ge Sn Pb) -&gt; Sentence &ldquo;<strong>C</strong>hemistry&nbsp;<strong>Si</strong>r&nbsp;<strong>G</strong>iv<strong>e</strong>s&nbsp;<strong>S</strong>a<strong>n</strong>ki&nbsp;<strong>P</strong>ro<strong>b</strong>lems&rdquo;</p><p>Sanki is a hindi word which mean crazy :P</p><p>I found this link useful as well&nbsp;<a href="http://www.wikihow.com/Memorise-the-Periodic-Table"></a><a href="http://www.wikihow.com/Memorise-the-Periodic-Table"></a><a href="http://www.wikihow.com/Memorise-the-Periodic-Table"></a><a href="http://www.wikihow.com/Memorise-the-Periodic-Table">http://www.wikihow.com/Memorise-the-Periodic-Table</a></p><p>The eagle genomics group provide an element of bioinformatics in periodic tables. Yes you got it, this is not periodic table rather bioinformatics tools with periodicals</p><p><a href="http://elements.eaglegenomics.com/"></a><a href="http://elements.eaglegenomics.com/"></a><a href="http://elements.eaglegenomics.com/"></a><a href="http://elements.eaglegenomics.com/">http://elements.eaglegenomics.com/</a></p><p>You can also try this video links, which provide you an overview with tricks on periodic tables:</p><p><a href="http://www.youtube.com/watch?v=fLSfgNxoVGk"></a><a href="http://www.youtube.com/watch?v=fLSfgNxoVGk"></a><a href="http://www.youtube.com/watch?v=fLSfgNxoVGk"></a><a href="http://www.youtube.com/watch?v=fLSfgNxoVGk">http://www.youtube.com/watch?v=fLSfgNxoVGk</a></p><p><a href="http://www.youtube.com/user/periodicvideos"></a><a href="http://www.youtube.com/user/periodicvideos"></a><a href="http://www.youtube.com/user/periodicvideos"></a><a href="http://www.youtube.com/user/periodicvideos">http://www.youtube.com/user/periodicvideos</a></p><p>For drug design educational material, software, tools, databses, viewer, file format and many more stuff at one place&nbsp;<a href="http://www.allfordrugs.com/drug-design/.%C2%A0I"></a><a href="http://www.allfordrugs.com/drug-design/"></a><a href="http://www.allfordrugs.com/drug-design/"></a><a href="http://www.allfordrugs.com/drug-design/">http://www.allfordrugs.com/drug-design/</a>&nbsp;I highly recommend you all computational drug designer to bookmark this page for future studies as well.</p><p>I just remember one of my mini project in which I use my flash knowledge (flash .. oh ya flash) to explain amino acids in interactive and user friendly manner. I can&rsquo;t provide It right now, but promise you to provide a link in near future. I hope that you will enjoy my flashy creative skills :).</p><p>Moreover, I found some of very interesting tricks to remember all amino acids chemical formulae on youtube at</p><p><a href="http://www.youtube.com/watch?v=gqrWb0fmzQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=gqrWb0fmzQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=gqrWb0fmzQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=gqrWb0fmzQ&amp;list=PL6132651E70BB5575">http://www.youtube.com/watch?v=gqrWb0fmzQ&amp;list=PL6132651E70BB5575</a></p><p><a href="http://www.youtube.com/watch?v=C2GfoGXfySQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=C2GfoGXfySQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=C2GfoGXfySQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=C2GfoGXfySQ&amp;list=PL6132651E70BB5575">http://www.youtube.com/watch?v=C2GfoGXfySQ&amp;list=PL6132651E70BB5575</a></p><p><br />Key points for computer added drug designers?<br />1. A shortage of biochemistry skills means that you absolutely nowhere in understanding the key concept and do research.<br />2. Keep handy with complex mathematical formula, before merely running tools or software.<br />3. Dig it better and deeper guys .. design it.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/32713/salzberg-lab</guid>
  <pubDate>Mon, 15 May 2017 05:14:01 -0500</pubDate>
  <link></link>
  <title><![CDATA[Salzberg lab]]></title>
  <description><![CDATA[
<p>We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.</p>

<p>https://salzberg-lab.org/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4003/personalised-medicine-animation</guid>
	<pubDate>Tue, 27 Aug 2013 10:07:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4003/personalised-medicine-animation</link>
	<title><![CDATA[Personalised Medicine - Animation]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/fEY3Khsmuak" frameborder="0" allowfullscreen></iframe>Two animated case scenarios set now and in the future. These highlight potential differences in the way patients are treated now, and how they might be treated as healthcare becomes more tailored.]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4552/imtech-lab</guid>
  <pubDate>Sun, 15 Sep 2013 09:41:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[IMTECH Lab]]></title>
  <description><![CDATA[
<p>Computer Aided Protein Structure Prediction; Identification of Vaccine<br />Candidates (T-Epitope prediction); Analysis of Nucleotide/Protein Sequences; Development of Web Server/</p>

<p>Software; Creation of Public Domain Resources in Biology<br />Present Status::</p>

<p>Developing prediction methods for gene, beta-turn, secondary structure and MHC-binding sites.<br />Area of Interest ::</p>

<p>Comparison of force field simulations. Analysis of DNA-protein interactions using molecular mechanics methods.Drug Target Identification using in silico biology.</p>

<p>More @ http://www.imtech.res.in/bic/index.php?option=com_content&amp;view=article&amp;id=65</p>

<p>PIs: http://www.imtech.res.in/bic/index.php?option=com_content&amp;view=article&amp;id=69</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/2336/3rd-annual-next-generation-sequencing-asia-congress-2013-at-singapore-singapore</guid>
  <pubDate>Wed, 14 Aug 2013 09:55:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[3rd Annual Next Generation Sequencing Asia Congress 2013 at Singapore, Singapore]]></title>
  <description><![CDATA[
<p>The 3rd Annual Next Generation Sequencing Asia Congress is to be held on the 22nd and 23rd of October 2013 in Singapore. Over the 2 days, the conference will provide an overview of the current options of next-generation sequencing platforms, technologies, applications and the newest computational tools for the analysis of next-generation sequencing data and analytical genomics as well as overcoming data management problems. The event will attract over 200 senior-level decision makers working in areas such as next generation sequencing, analytical genomics, computational biology, oncology, RNA profiling, molecular genomics, biomarkers, bioinformatics &amp; data management and clinical &amp; diagnostics development.</p>

<p>Dated : 22 Nov 2013 -23 Nov 2013</p>

<p>http://www.ngsasia-congress.com/</p>
]]></description>
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