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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28842?offset=690</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/12989/center-for-molecular-dynamics-nepal-cmdn-nepal</guid>
  <pubDate>Wed, 23 Jul 2014 13:54:51 -0500</pubDate>
  <link></link>
  <title><![CDATA[Center for Molecular Dynamics Nepal (CMDN), Nepal]]></title>
  <description><![CDATA[
<p>Center for Molecular Dynamics Nepal (CMDN), established 2007 prides itself as a research driven nongovernmental organization. Unlike other civil society organizations, CMDN is dedicated entirely to promoting research in the country. With its team of energetic and highly motivated experts, CMDN is now recognized as the leading public health and wildlife research organization of the country.</p>

<p>More at http://www.cmdn.org.np/main/index.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36997/cgview-circular-genome-viewer</guid>
	<pubDate>Wed, 20 Jun 2018 10:15:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36997/cgview-circular-genome-viewer</link>
	<title><![CDATA[CGView - Circular Genome Viewer]]></title>
	<description><![CDATA[CGView is a Java package for generating high quality, zoomable maps of circular genomes. Its primary purpose is to serve as a component of sequence annotation pipelines, as a means of generating visual output suitable for the web. Feature information and rendering options are supplied to the program using an XML file, a tab delimited file, or an NCBI ptt file. CGView converts the input into a graphical map (PNG, JPG, or Scalable Vector Graphics format), complete with labels, a title, legends, and footnotes. In addition to the default full view map, the program can generate a series of hyperlinked maps showing expanded views. The linked maps can be explored using any web browser, allowing rapid genome browsing, and facilitating data sharing. The feature labels in maps can be hyperlinked to external resources, allowing CGView maps to be integrated with existing web site content or databases. For examples of the various output types, see the CGView gallery.

http://wishart.biology.ualberta.ca/cgview/gallery.html

http://stothard.afns.ualberta.ca/downloads/CCT/index.html

https://www.gview.ca/wiki/GView/WebHome

https://server.gview.ca/

http://stothard.afns.ualberta.ca/cgview_server/

Paper https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbx081/4037458<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>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13276/senior-research-fellow-at-nit-rourkela</guid>
  <pubDate>Wed, 30 Jul 2014 00:53:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Research Fellow at NIT, Rourkela]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF TECHNOLOGY, ROURKELA – 769 008(ORISSA)<br />SPONSORED RESEARCH, INDUSTRIAL CONSULTANCY &amp; CONTINUING EDUCATION</p>

<p>ADVERTISEMENT NO: NITR/SR/CH-BIF/2014/30</p>

<p>Applications are invited on prescribed format for the following assignment in a purely time bound research project undertaken in the Department of Biotechnology &amp; Medical Engineering of the Institute.</p>

<p>1. Name of the Temporary Post : Senior Research Fellow-01<br />2. Name of the Research Project: “ Bioinformatics Infrastructure Facility (BIF)”<br />3. Name of the Sponsoring Agency: DBT, Government of India, 4 Tenure of the Project : 12th Five year Plan<br />5 Tenure of the Assignment : 01 year [Likely to be extended for 04 more years]<br />6 Job Description : BIF Maintenance and Active Research in Bioinformatics<br />7. Consolidated monthly compensation / Fellowship: Rs.18,000/- P.M.</p>

<p>8. Essential Qualifications and experience: B.Tech with valid GATE Score or M.Tech degree in Biotechnology/Bioinformatics/Computer Science/Computational Biology<br />9. Desirable Qualifications/ Experiences: Experience of Programming in PERL,R, Python, Unix and Visual Studio + Knowledge in NGS data analysis work flows ,WGS and statistical packages such as CRAN-R,MATLAB etc.</p>

<p>10. Accommodation : Bachelor accommodation in the Institute may be provided subject to availability.<br />11. For technical information on the project, the candidate may contact the Principal Investigator at the following address:</p>

<p>Name : Prof. Mukesh K Gupta<br />Address : Dept. of Biotechnology &amp; Medical Engineering,<br />N.I.T.Rourkela-769 008<br />Telephone No : 0661-2462294<br />E-mail : guptam@nitrkl.ac.in</p>

<p>Eligible persons may apply in the prescribed format (available in the Institute Website)affixed with coloured photographs to be submitted in duplicate along with photo copies of relevant certificates, grade/ mark sheets, publications etc., to Asst. Registrar, SRICCE,<br />National Institute of Technology, Rourkela–769 008 before 22.08.2014. The cover should be super- scribed clearly the post applied for &amp; Name of the Project.</p>

<p>Mere possession of minimum qualification does not guarantee invitation to the interview.<br />Candidates will be short listed based on merit and need of the project.</p>

<p>Advertisement:</p>

<p>http://www.nitrkl.ac.in/IntraWeb/Jobs_Tenders/Jobs/ProjectFellowship/2014/141707192838_1.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37984/baum-%E2%80%93-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus</guid>
	<pubDate>Wed, 24 Oct 2018 23:35:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37984/baum-%E2%80%93-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus</link>
	<title><![CDATA[BAUM – Improving Genome Assembly by Adaptive Unique Mapping and Local Overlap-Layout-Consensus]]></title>
	<description><![CDATA[<p><span>BAUM, breaks the whole genome into regions by adaptive unique mapping; then the local OLC is used to assemble each region in parallel. BAUM can: (1) perform reference-assisted assembly based on the genome of a close species; (2) or improve the results of existing assemblies that are obtained based on short or long sequencing reads.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus/" rel="nofollow">http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/13523/megadock-40</guid>
	<pubDate>Thu, 07 Aug 2014 18:08:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/13523/megadock-40</link>
	<title><![CDATA[MEGADOCK 4.0]]></title>
	<description><![CDATA[<p>An ultra&ndash;high-performance protein&ndash;protein docking software for heterogeneous supercomputers</p>
<p id="p-4"><strong>Summary:</strong> The application of protein&ndash;protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of over 97% strong scaling.</p>
<p id="p-5"><strong>Availability and Implementation:</strong> MEGADOCK 4.0 is written in C++ with OpenMPI and NVIDIA CUDA 5.0 (or later) and is freely available to all academic and non-profit users at: <a href="http://www.bi.cs.titech.ac.jp/megadock">http://www.bi.cs.titech.ac.jp/megadock</a>.</p>
<p id="p-6"><strong>Contact:</strong> <a href="mailto:akiyama@cs.titech.ac.jp">akiyama@cs.titech.ac.jp</a></p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short</a></p>]]></description>
	<dc:creator>Suleman Khan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/38418/charles-swanton-lab</guid>
  <pubDate>Tue, 11 Dec 2018 08:09:22 -0600</pubDate>
  <link></link>
  <title><![CDATA[CHARLES SWANTON LAB]]></title>
  <description><![CDATA[
<p>They are using the latest DNA sequencing technology to read the genetic makeup of cancer cells within tumours in ever greater detail, teasing out patterns of evolution (evolutionary rule books), cancer heterogeneity and working out what changes have happened as a tumour evolves. We’re also investigating the processes that cause mutations and accelerate tumour evolution and working out how they might be stopped. And we are running evolutionary clinical trials with immune and targeted therapies to bring the benefits of our work to patients as quickly as possible.</p>

<p>https://www.crick.ac.uk/research/labs/charles-swanton</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14024/grapher</guid>
	<pubDate>Thu, 14 Aug 2014 14:02:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14024/grapher</link>
	<title><![CDATA[GrapheR !!!]]></title>
	<description><![CDATA[<p>What a wonderful gem <em>GrapheR</em> is.... Oh yes it is. <em>GrapheR</em> is a GUI for base graphics in R by http://www.maximeherve.com/. The package provides a graphical user interface for creating base charts in R. It is ideal for beginners in R, as the user interface is very clear and the code is written along side into a text file, allowing users to recreate the charts directly in the console. <br /><br />Adding and changing legends? Messing around with the plotting window settings? It is much easier/quicker with this GUI than reading the help file and trying to understand the various parameters.<br />Here is a little example using the iris data set.<br /><br />library(GrapheR)<br />data(iris)<br />run.GrapheR()<br /><br />This will bring up a window that helps me to create the chart and tweak the various parameters.</p><p><img src="http://4.bp.blogspot.com/-NbnCM1dPh3E/U9aW9YxJ9oI/AAAAAAAABgo/gEPzPhOpf2Y/s1600/GrapheR.png" alt="image" width="878" height="868" style="border: 0px; border: 0px;"><br /><br />Finally, I find the underlying R code in a file created by <em>GrapheR</em>. For more details read also the <a href="http://cran.r-project.org/web/packages/GrapheR/index.html" target="_blank">package vignette</a>, which is available in <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_en.pdf" target="_blank">English</a>, <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_fr.pdf" target="_blank">French</a> and <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_de.pdf" target="_blank">German</a>!</p>]]></description>
	<dc:creator>John Parker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38735/genome-assembly-tutorial-genome-assembly-for-short-and-long-reads</guid>
	<pubDate>Sat, 19 Jan 2019 17:29:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38735/genome-assembly-tutorial-genome-assembly-for-short-and-long-reads</link>
	<title><![CDATA[Genome assembly tutorial &quot;Genome Assembly for short and long reads&quot;]]></title>
	<description><![CDATA[<p>In this lab we will perform de novo genome assembly of a bacterial genome. You will be guided through the genome assembly starting with data quality control, through to building contigs and analysis of the results. At the end of the lab you will know:</p>
<ol>
<li>How to perform basic quality checks on the input data</li>
<li>How to run a short read assembler on Illumina data</li>
<li>How to run a long read assembler on Pacific Biosciences or Oxford Nanopore data</li>
<li>How to improve the accuracy of a long read assembly using short reads</li>
<li>How to assess the quality of an assembly</li>
</ol>
<p>https://bioinformaticsdotca.github.io/high-throughput_biology_2017</p><p>Address of the bookmark: <a href="https://bioinformaticsdotca.github.io/high-throughput_biology_2017_module6_lab" rel="nofollow">https://bioinformaticsdotca.github.io/high-throughput_biology_2017_module6_lab</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14186/pybedtools</guid>
	<pubDate>Wed, 20 Aug 2014 01:03:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14186/pybedtools</link>
	<title><![CDATA[pybedtools]]></title>
	<description><![CDATA[<p>pybedtools is a Python wrapper for Aaron Quinlan's BEDtools programs (https://github.com/arq5x/bedtools), which are widely used for genomic interval manipulation or "genome algebra". pybedtools extends BEDTools by offering feature-level manipulations from with Python. See full online documentation, including installation instructions, at http://pythonhosted.org/pybedtools/.</p><p>More at http://pythonhosted.org/pybedtools/</p><p>A powerful toolset for genome arithmetic.http://code.google.com/p/bedtools/</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</guid>
	<pubDate>Sat, 13 Apr 2019 08:55:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</link>
	<title><![CDATA[Darwin-WGA: A Co-processor Provides Increased Sensitivity in Whole Genome Alignments with High Speedup]]></title>
	<description><![CDATA[<p>Darwin-WGA, is the first hardware accelerator for whole genome alignment and accelerates the gapped filtering stage. Darwin-WGA also employs GACT-X, a novel algorithm used in the extension stage to align arbitrarily long genome sequences using a small on-chip memory, that provides better quality alignments at 2&times; improvement in memory and speed over the previously published GACT algorithm. Implemented on an FPGA, Darwin-WGA provides up to 24&times; improvement (performance/$) in WGA over iso-sensitive software.</p>
<p><a href="https://stanford.edu/~yatisht/pubs/darwin-wga.pdf">https://stanford.edu/~yatisht/pubs/darwin-wga.pdf</a></p><p>Address of the bookmark: <a href="https://github.com/gsneha26/Darwin-WGA" rel="nofollow">https://github.com/gsneha26/Darwin-WGA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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