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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30901?offset=1000</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11035/bioinformatics-jrfsrf-position-at-nii</guid>
  <pubDate>Sun, 25 May 2014 16:54:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/SRF position at NII]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF IMMUNOLOGY, NEW DELHI-110067</p>

<p>Applications are invited for the position of Senior Research Fellow for the following time-bound sponsored project as per the details given below:</p>

<p>1. BTIS project on, “Bioinformatics Center-National Infrastructural Facility in the Area of Immunology” funded by DBT</p>

<p>Senior Research Fellow (P) (One Position only)</p>

<p>Dr. Debasisa Mohanty<br />Staff Scientist-VI<br />deb@nii.res.in</p>

<p>Qualifications: M.Sc in Biological Sciences or Biotechnology with at least 04 years of Research experience in Bioinformatics or computational Biology after the master’s degree is essential.</p>

<p>Emoluments: The selected candidates will draw consolidated emoluments as per Institute Rules, depending upon qualifications &amp; experience</p>

<p>Rs. 18,000/- per month consolidated plus 30% HRA if Leading to Ph.D/NET/GATE Qualified otherwise Rs. 14,000/- per month + 30% HRA.</p>

<p>Job description: The candidate should be well versed in programming in PERL/C++/HTML/CGI, web server and portal development, computational analysis of<br />protein structure &amp; function, molecular dynamics simulations and use of high performance computing systems.</p>

<p>GENERAL TERMS AND CONDITIONS:-</p>

<p>1. The candidates selected for the above posts will be on contract for one year or duration of the project whichever is shorter, at a time.<br />2. No hostel/ housing facility will be provided.<br />3. Number of posts may vary and shall be need based. Advertisement is no commitment.<br />4. Applicants may clearly mention the category they belong to i.e. SC/ST/OBC/PH and attach documentary proof of the same.<br />5. No TA/DA will be paid for attending the interview, if called for.<br />6. Apart from sending application in the prescribed format given below, candidates should send complete Curriculum Vitae along with the names of three referees. Curriculum Vitae should contain details of the experimental expertise.</p>

<p>HOW TO APPLY Interested candidates may apply directly, STRICTLY IN THE PRESCRIBED FORMAT GIVEN BELOW, through e-mail, to the Investigator of the project, clearly indicating the name of the project along with their complete C.V., e-mail id, fax numbers, telephone numbers. Only Short listed candidates will be called for interview and they required to submit attested copies of all their certificates and a Demand Draft of Rs 100/- drawn on Canara Bank or Indian Bank payable at Delhi/New Delhi in favour of the Director, NII (SC / ST and PH candidates are exempted subject to submission of documentary proof), at the time of interview.</p>

<p>LAST DATE OF RECEIPT OF APPLICATIONS: 06th June, 2014</p>

<p>Advertisement</p>

<p>www1.nii.res.in/sites/default/files/projectappointment-Dr.Mohanty-6June2014.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/1178/r-package-for-visualising-go-enrichment</guid>
	<pubDate>Mon, 22 Jul 2013 12:25:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/1178/r-package-for-visualising-go-enrichment</link>
	<title><![CDATA[R package for visualising GO enrichment]]></title>
	<description><![CDATA[<p>An R package that visualizes the GO enrichment results as word clouds and arranges them together with figures of experimental data. This allows us to draw informative summary plots for analyses such as differential expression or clustering, where for each gene list we display its behaviour in the experiment alongside with its GO annotations.</p><p>Links @ http://raivokolde.github.io/GOsummaries/</p><p>Lab @ http://biit.cs.ut.ee/about/main</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13014/bioinformatics-jrf-vacancy-at-icgeb-new-delhi</guid>
  <pubDate>Wed, 23 Jul 2014 16:07:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF vacancy at ICGEB, New Delhi]]></title>
  <description><![CDATA[
<p>Junior Research Fellow for a DBT sponsored project entitled "Computational and experimental characterization of stage specific arginine methylation in P. falciparum proteome". </p>

<p>Candidates should have a 1st class MSc/MTech/BTech degree in Bioinformatics. Please send complete CV, quoting Application for RMETH-JRF-2014, by email to Dr. Dinesh Gupta: dinesh@icgeb.res.in</p>

<p>Closing date for applications: 6 August 2014</p>

<p>More at http://www.icgeb.org/tl_files/Vacancies/JRF.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/18738/surrogate-variable-analysis-sva</guid>
	<pubDate>Thu, 30 Oct 2014 08:01:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/18738/surrogate-variable-analysis-sva</link>
	<title><![CDATA[Surrogate Variable Analysis (SVA)]]></title>
	<description><![CDATA[<p>The sva package contains functions for removing batch effects and other unwanted variation in high-throughput experiment. Specifically, the sva package contains functions for the identifying and building surrogate variables for high-dimensional data sets. Surrogate variables are covariates constructed directly from high-dimensional data (like gene expression/RNA sequencing/methylation/brain imaging data) that can be used in subsequent analyses to adjust for unknown, unmodeled, or latent sources of noise. The sva package can be used to remove artifacts in three ways:</p><p>(1) identifying and estimating surrogate variables for unknown sources of variation in high-throughput experiments (Leek and Storey 2007 PLoS Genetics,2008 PNAS),</p><p>(2) directly removing known batch effects using ComBat (Johnson et al. 2007 Biostatistics) and</p><p>(3) removing batch effects with known control probes (Leek 2014 biorXiv).</p><p>Removing batch effects and using surrogate variables in differential expression analysis have been shown to reduce dependence, stabilize error rate estimates, and improve reproducibility, see (Leek and Storey 2007 PLoS Genetics, 2008 PNAS or Leek et al. 2011 Nat. Reviews Genetics).</p><p>More at http://www.bioconductor.org/packages/release/bioc/html/sva.html</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11313/linux-sort-commands-for-bioinformatics</guid>
	<pubDate>Sat, 31 May 2014 15:41:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11313/linux-sort-commands-for-bioinformatics</link>
	<title><![CDATA[Linux Sort Commands for Bioinformatics]]></title>
	<description><![CDATA[<p>Almost all the scripting languages such as Perl, Python etc have built-in sort, but unfortunately none of them are as flexible as sort command. But one when it come to space efficiency GNU sort stands at the top. It can sort a 20Gb file with less than 2Gb memory. It is not trivial to implement so powerful a sort by yourself.</p><p>sort a space-delimited file based on its first column, then the second if the first is the same, and so on:<br />sort input.txt</p><p>sort a huge file (GNU sort ONLY):<br />sort -S 1500M -t $HOME/tmp input.txt &gt; sorted.txt</p><p>sort starting from the third column, skipping the first two columns:<br />sort +2 input.txt</p><p>sort the second column as numbers, descending order; if identical, sort the 3rd as strings, ascending order:<br />sort -k2,2nr -k3,3 input.txt</p><p>sort starting from the 4th character at column 2, as numbers:<br />sort -k2.4n input.txt</p><p>More Linxu sort command information<br /><br />If you have any sort commands you'd like to share, please add them to our comments section below. For more help, you can also type:<br /><br />man sort<br /><br />or<br /><br />sort --help<br /><br />on your Unix/Linux system.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33592/circular-plots-in-r</guid>
	<pubDate>Mon, 19 Jun 2017 06:20:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33592/circular-plots-in-r</link>
	<title><![CDATA[Circular plots in R]]></title>
	<description><![CDATA[<div>
<p><strong>Circular plots</strong>&nbsp;are useful to represent complicated informations. They are used in 2 specific cases: when you have long axis and numerous categories, and when you want to show relationships between elements. The&nbsp;<a href="http://circos.ca/images/samples/" target="_blank">circos gallery</a>&nbsp;displays several examples of circular plots, what gives a nice overview of the possibilities. Circos is the most famous</p>
</div>
<div>
<p>tool to create circular plots. Thanks to&nbsp;<a href="https://www.linkedin.com/in/zuguanggu" target="_blank">Zuguang Gu</a>, the&nbsp;<a href="https://cran.r-project.org/web/packages/circlize/vignettes/circlize.pdf" target="_blank">Circlize library</a>&nbsp;makes the circos functions available in R! It implements low-level graphic functions for adding common graphics in a circular layout. This page aims to learn you how to use the library, so I strongly advise to read the graphics in the proposed order!</p>
<p><img src="http://www.r-graph-gallery.com/wp-content/uploads/2016/03/122_Circlize_package.png" width="480" height="480" alt="image" style="border: 0px;"></p>
</div>
<p>http://www.r-graph-gallery.com/portfolio/circular-plot/</p><p>Address of the bookmark: <a href="http://www.r-graph-gallery.com/portfolio/circular-plot/" rel="nofollow">http://www.r-graph-gallery.com/portfolio/circular-plot/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34396/pore-an-r-package-for-the-visualization-and-analysis-of-nanopore-sequencing-data</guid>
	<pubDate>Thu, 23 Nov 2017 09:55:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34396/pore-an-r-package-for-the-visualization-and-analysis-of-nanopore-sequencing-data</link>
	<title><![CDATA[poRe: an R package for the visualization and analysis of nanopore sequencing data]]></title>
	<description><![CDATA[<p><strong>Motivation:</strong>&nbsp;The Oxford Nanopore MinION device represents a unique sequencing technology. As a mobile sequencing device powered by the USB port of a laptop, the MinION has huge potential applications. To enable these applications, the bioinformatics community will need to design and build a suite of tools specifically for MinION data.</p>
<p><strong>Results:</strong>&nbsp;Here we present poRe, a package for R that enables users to manipulate, organize, summarize and visualize MinION nanopore sequencing data. As a package for R, poRe has been tested on Windows, Linux and MacOSX. Crucially, the Windows version allows users to analyse MinION data on the Windows laptop attached to the device.</p>
<p><strong>Availability and implementation:</strong>&nbsp;poRe is released as a package for R at&nbsp;<a href="http://sourceforge.net/projects/rpore/" target="">http://sourceforge.net/projects/rpore/</a>&nbsp;. A tutorial and further information are available at&nbsp;<a href="https://sourceforge.net/p/rpore/wiki/Home/" target="">https://sourceforge.net/p/rpore/wiki/Home/</a></p>
<p><strong>Contact:</strong><a href="mailto:mick.watson@roslin.ed.ac.uk" target="">mick.watson@roslin.ed.ac.uk</a></p><p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/31/1/114/2365693" rel="nofollow">https://academic.oup.com/bioinformatics/article/31/1/114/2365693</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11494/postdoc-position-at-centre-mediterraneen-de-medecine-moleculaire-nice-france</guid>
  <pubDate>Wed, 04 Jun 2014 07:20:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc position at Centre Méditerranéen de Médecine Moléculaire - Nice - France]]></title>
  <description><![CDATA[
<p>The research group of Dr. Michele Trabucchi at the Centre Méditerranéen de Médecine Moléculaire (C3M) at INSERM U1065 (University of Nice Sophia-Antipolis, France) is seeking candidates for a Postdoctoral fellow position to start on October 2014 for 3 years funded by FRM (Fondation pour la Recherche Médicale).<br />The broad interest of the lab is in understanding the expression control and function of small RNAs in activated myeloid cells (visit our webpage to check research interests and publications of the group : http://www.unice.fr/c3m/EN/Equipe10.html ). </p>

<p>The work will focus on the functional studies of small RNAs by using next-generation sequencing approaches.<br /> <br />Candidates should hold a Ph.D. degree and have strong background in bioinformatics.<br />The University of Nice Sophia-Antipolis provides a wide range of facilities and training essential for biomedical research.</p>

<p>Interested applicants should send a PDF with a cover letter stating research interests and qualifications, an updated CV, a summary of previous research experience and contact information for two references to Michele Trabucchi ( mtrabucchi@unice.fr )</p>

<p>Homepage: http://www.unice.fr/c3m/EN/Equipe10.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35437/dupradar-package</guid>
	<pubDate>Sun, 04 Feb 2018 14:28:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35437/dupradar-package</link>
	<title><![CDATA[dupRadar package]]></title>
	<description><![CDATA[<p><span>The&nbsp;</span><em>dupRadar</em><span>&nbsp;package gives an insight into the duplication problem by graphically relating the gene expression level and the duplication rate present on it. Thus, failed experiments can be easily identified at a glance</span></p><p>Address of the bookmark: <a href="https://bioconductor.org/packages/3.7/bioc/vignettes/dupRadar/inst/doc/dupRadar.html" rel="nofollow">https://bioconductor.org/packages/3.7/bioc/vignettes/dupRadar/inst/doc/dupRadar.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</guid>
	<pubDate>Sun, 08 Jun 2014 10:06:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</link>
	<title><![CDATA[Ten recommendations for creating usable bioinformatics command line software]]></title>
	<description><![CDATA[<p><span>Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used. Here I present ten recommendations for command line software author&rsquo;s tools to follow, which I believe would greatly improve the uptake and usability of their products, waste less user&rsquo;s time, and improve the quality of scientific analyses.</span></p><p>Address of the bookmark: <a href="http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer" rel="nofollow">http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer</a></p>]]></description>
	<dc:creator>RAJESH DETROJA</dc:creator>
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