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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30236?offset=330</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29208/srf-bioinformatics-job-position-in-national-institute-of-plant-genome-research-nipgr</guid>
  <pubDate>Mon, 19 Sep 2016 05:43:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)]]></title>
  <description><![CDATA[
<p>SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)<br />Title : “Transcriptome and small RNA diversity analysis of developing seed contrasting rice varieties” <br />Qualification : Candidates having M.Sc./M.Tech. degree or equivalent (with minimum 60% marks) in Bioinformatics with a minimum of two years of post M.Sc./M.Tech research experience are eligible to apply.<br />No. of Post : 01<br />How to apply<br />Application should reach to Dr. Pinky Agarwal, Staff Scientist, National Institute of Plant Genome Research (NIPGR) Aruna Asaf Ali Marg, P.O. Box NO. 10531, New Delhi - 110067 on or before 30/09/2016</p>

<p>More at http://www.nipgr.res.in/careers/vacancies_latest.php#</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29210/cgview-circular-genome-viewer</guid>
	<pubDate>Mon, 19 Sep 2016 07:52:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29210/cgview-circular-genome-viewer</link>
	<title><![CDATA[CGView - Circular Genome Viewer]]></title>
	<description><![CDATA[<p>GView is a Java package used to display and navigate bacterial genomes. GView is useful for producing high-quality genome maps for use in publications and websites, or as a visualization tool in a sequence annotation pipeline. Users can interact with the genome using a powerful pan-and-zoom interface, or GView can write static images of a genome to a file. GView can draw a genome using either circular or linear layouts. For examples of some of the images GView can produce, see the <a href="https://www.gview.ca/bin/view/GView/ImageGallery">Image Gallery</a>. GView is a re-write of <a href="http://wishart.biology.ualberta.ca/cgview/" target="_top">CGView</a>, a circular genome viewer written by Paul Stothard. The goal of GView is to provide greater user interaction, and more flexibility in how the genome map is rendered. To aid with easily configuring the display of a genome, a style editor has been included to provide an intuitive, user-friendly graphical user interface for customizing genome maps. Styling attributes such as colours or fonts for the various map elements can be adjusted in real time. Customized styles can be saved for later use or for application to other genome maps using GView's <a href="https://www.gview.ca/bin/view/GViewDocumentation/GViewGSS">custom file format</a>.</p><p>Address of the bookmark: <a href="http://wishart.biology.ualberta.ca/cgview/" rel="nofollow">http://wishart.biology.ualberta.ca/cgview/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29270/blast-ring-image-generator-brig</guid>
	<pubDate>Fri, 30 Sep 2016 09:18:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29270/blast-ring-image-generator-brig</link>
	<title><![CDATA[BLAST Ring Image Generator (BRIG)]]></title>
	<description><![CDATA[<p>BRIG is a free cross-platform (Windows/Mac/Unix) application that can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data. The application is available at: <a href="http://sourceforge.net/projects/brig">http://sourceforge.net/projects/brig</a></p>
<p>If you have any questions or comments, post them on <a href="http://sourceforge.net/tracker/?group_id=328245">one of the trackers</a> on BRIG&rsquo;s SourceForge page: <a href="http://sourceforge.net/tracker/?group_id=328245">http://sourceforge.net/tracker/?group_id=328245</a>.</p>
<p>Features:</p>
<ul>
<li>Images show similarity between a central reference sequence and other sequences as concentric rings.</li>
<li>BRIG will perform all BLAST comparisons and file parsing automatically via a simple GUI.</li>
<li>Contig boundaries and read coverage can be displayed for draft genomes; customized graphs and annotations can be displayed.</li>
<li>Using a user-defined set of genes as input, BRIG can display gene presence, absence, truncation or sequence variation in a set of complete genomes, draft genomes or even raw, unassembled sequence data.</li>
<li>BRIG also accepts SAM-formatted read-mapping files enabling genomic regions present in unassembled sequence data from multiple samples to be compared simultaneously</li>
</ul><p>Address of the bookmark: <a href="http://brig.sourceforge.net/" rel="nofollow">http://brig.sourceforge.net/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29379/bbmap-help</guid>
	<pubDate>Mon, 10 Oct 2016 06:29:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29379/bbmap-help</link>
	<title><![CDATA[BBMap help]]></title>
	<description><![CDATA[<div>
<div>BBMAP <span> &bull; <span>a solution for everything</span></span><a href="https://www.biostarhandbook.com/"><span></span></a></div>
<div>That content has been reformatted and it is being expanded to include more information.<span><span></span></span></div>
</div>
<hr>
<p>There are common options for most BBMap suite programs and depending on the file extension the input/output format is automatically chosen/set.</p>
<hr>
<h3>Using BBMap</h3>
<h4>Mapping Nanopore reads</h4>
<p>BBMap.sh has a length cap of 6kbp. Reads longer than this will be broken into 6kbp pieces and mapped independently.</p>
<p>More at https://www.biostarhandbook.com/tools/bbmap/bbmap-help.html</p><p>Address of the bookmark: <a href="https://www.biostarhandbook.com/tools/bbmap/bbmap-help.html" rel="nofollow">https://www.biostarhandbook.com/tools/bbmap/bbmap-help.html</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29583/graph-genome-suite</guid>
	<pubDate>Fri, 28 Oct 2016 07:59:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29583/graph-genome-suite</link>
	<title><![CDATA[Graph Genome Suite]]></title>
	<description><![CDATA[<p><span>Seven Bridges is the biomedical data analysis company accelerating breakthroughs in genomics research for cancer, drug development and precision medicine. We build self-improving systems to analyze millions of genomes, including the&nbsp;</span><strong>Graph Genome Suite</strong><span>&nbsp;&mdash; the most advanced population genomics tools in the world.</span></p><p>Address of the bookmark: <a href="https://www.sbgenomics.com/graph/" rel="nofollow">https://www.sbgenomics.com/graph/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29995/hga</guid>
	<pubDate>Tue, 29 Nov 2016 07:25:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29995/hga</link>
	<title><![CDATA[HGA]]></title>
	<description><![CDATA[<p>HGA tool version 1.0 This tool helps to apply the Hierarchical Genome Assembly (HGA) method. The tool will apply: 1. Partitioning a given reads dataset into a given number of partitions. 2. Assembling each partitions using a pre-specified assembler (Velvet or SPAdes in this version) and using a given kmer size. 3. Merging all the assemblies of the partition. 4. Combining all the assemblies of the partition (using velvet with kmer value of 31). 5. Finaly, re-assembling the whole dataset with the merged contigs or the combined contigs, using a given kmer size.</p>
<p>https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA</p><p>Address of the bookmark: <a href="https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA" rel="nofollow">https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30015/scripts</guid>
	<pubDate>Wed, 30 Nov 2016 10:35:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30015/scripts</link>
	<title><![CDATA[Scripts]]></title>
	<description><![CDATA[<p>Useful script for NGS analysis.</p><p>Address of the bookmark: <a href="http://augustus.gobics.de/binaries/scripts/" rel="nofollow">http://augustus.gobics.de/binaries/scripts/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30085/fqtools</guid>
	<pubDate>Thu, 08 Dec 2016 09:31:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30085/fqtools</link>
	<title><![CDATA[fqtools]]></title>
	<description><![CDATA[<p><code>fqtools</code><span>&nbsp;is a software suite for fast processing of&nbsp;</span><code>FASTQ</code><span>&nbsp;files. Various file manipulations are supported. See below for a full list of the subcommands available and a brief description of their purpose. Most of the individual subcommands will take either a single file or a pair of files as input. If no input file is specified, fqtools will attempt to read data from&nbsp;</span><code>stdin</code><span>. In this case, it is advisabe to specify the format of the data provided. For subcommands that generate FASTQ data, either a single file or a pair of files will be generated. If no&nbsp;</span><code>-o</code><span>&nbsp;argument is provided, single files will be writted to&nbsp;</span><code>stdout</code><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/alastair-droop/fqtools" rel="nofollow">https://github.com/alastair-droop/fqtools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30147/cisa-contig-integrator-for-sequence-assembly</guid>
	<pubDate>Thu, 15 Dec 2016 05:42:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30147/cisa-contig-integrator-for-sequence-assembly</link>
	<title><![CDATA[CISA: Contig Integrator for Sequence Assembly]]></title>
	<description><![CDATA[<p>A plethora of algorithmic assemblers have been proposed for the <em>de novo</em> assembly of genomes, however, no individual assembler guarantees the optimal assembly for diverse species. Optimizing various parameters in an assembler is often performed in order to generate the most optimal assembly. However, few efforts have been pursued to take advantage of multiple assemblies to yield an assembly of high accuracy. In this study, we employ various state-of-the-art assemblers to generate different sets of contigs for bacterial genomes. A tool, named CISA, has been developed to integrate the assemblies into a hybrid set of contigs, resulting in assemblies of superior contiguity and accuracy, compared with the assemblies generated by the state-of-the-art assemblers and the hybrid assemblies merged by existing tools. This tool is implemented in Python and requires MUMmer and BLAST+ to be installed on the local machine. The source code of CISA and examples of its use are available at <a href="http://sb.nhri.org.tw/CISA/">http://sb.nhri.org.tw/CISA/</a>.</p><p>Address of the bookmark: <a href="http://sb.nhri.org.tw/CISA/en/CISA" rel="nofollow">http://sb.nhri.org.tw/CISA/en/CISA</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30249/genome-assembly-tutorial</guid>
	<pubDate>Tue, 20 Dec 2016 07:56:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30249/genome-assembly-tutorial</link>
	<title><![CDATA[Genome Assembly Tutorial]]></title>
	<description><![CDATA[<p><span>If genomes were completely random sequences in a statistical sense, 'overlap-consensus-layout' method would have been enough to assemble large genomes from Sanger reads. In contrast, real genomes often have long repetitive regions, and they are hard to assemble using overlap-consensus-layout approach. De Bruijn graph-based assembly approach was originally proposed to handle the assembly of repetitive regions better.</span></p>
<p><span>More at&nbsp;http://www.homolog.us/Tutorials/index.php?p=1.4&amp;s=1</span></p><p>Address of the bookmark: <a href="http://www.homolog.us/Tutorials/index.php?p=1.4&amp;s=1" rel="nofollow">http://www.homolog.us/Tutorials/index.php?p=1.4&amp;s=1</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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