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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38443?offset=140</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44182/collection-of-graph-visualization-tools</guid>
	<pubDate>Wed, 25 Jan 2023 02:57:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44182/collection-of-graph-visualization-tools</link>
	<title><![CDATA[Collection of Graph Visualization tools !]]></title>
	<description><![CDATA[<p>Standard approaches to genome inference and analysis relate sequences to a single linear reference genome. This is efficient but has a fundamental problem: Differences from this reference are hard to observe and describe in a coherent way. Variation and sequence are separated.</p>
<p><a href="https://pangenome.github.io/images/genomic-vs-pangenomic-analysis.png"><img src="https://pangenome.github.io/images/genomic-vs-pangenomic-analysis.png" alt="image" width="45%" style="border: 0px; border: 0px;"></a><span>&nbsp;</span><a href="https://pangenome.github.io/images/genomic-vs-pangenomic-models.png"><img src="https://pangenome.github.io/images/genomic-vs-pangenomic-models.png" alt="image" width="54%" style="border: 0px; border: 0px;"></a></p>
<p><a href="https://fungidb.org/fungidb/app/downloads/Current_Release/GultimumBR650/" target="_blank">https://fungidb.org/fungidb/app/downloads/Current_Release/GultimumBR650/</a></p><p>Address of the bookmark: <a href="https://pangenome.github.io/" rel="nofollow">https://pangenome.github.io/</a></p>]]></description>
	<dc:creator>Neel</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/opportunity/view/27945/srf-project-assistant-bioinformatics-at-nirrh</guid>
  <pubDate>Sun, 19 Jun 2016 09:11:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF/ Project Assistant Bioinformatics at NIRRH]]></title>
  <description><![CDATA[
<p>SRF/ Project Assistant Bioinformatics recruitment in National Institute for Research in Reproductive Health (NIRRH)</p>

<p>Title of Project : 1. “Analysis Of The Structures Of Known Antimicrobial Peptides Using Machine Learning Algoitms And Molecular Dynamics Simulations”</p>

<p>Senior Research Fellow /1 Post</p>

<p>Qualification: First class M.Sc. in Bioinformatics/ Biological Sciences from recognized university with 2 years research experience and CSIR/UGC/ICMR net qualified OR First class M.Sc. in Bioinformatics/ Biological Sciences from recognized university with 2 years research experience Research experience in bioinformatics and wetlab methods. </p>

<p>Age: Not exceeding 35 Years</p>

<p>Pay Scale : Rs.18,000/- + 30% HRA Rs.14,000/- + 30% HRA </p>

<p>Project Assistant (Level-II) /1 Post</p>

<p>Qualification:  First class M.Sc. in Bioinformatics/ Biological Sciences/Computer Sciences Training experience in bioinformatics and wetlab methods .</p>

<p>Age: Not exceeding 28 Years </p>

<p>Pay Scale : Rs.8,000<br />How to apply<br />Candidates must bring along with them all the relevant documents in original and one set of attested photocopies of the same and one passport size recent colour photograph. </p>

<p>Walk-in-Interview on 28.06.2016 between 09:00 hrs. to 12:00 hrs.</p>

<p>More at http://www.nirrh.res.in/links/job_oppotunities.htm</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41202/biocontainers</guid>
	<pubDate>Thu, 20 Feb 2020 05:29:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41202/biocontainers</link>
	<title><![CDATA[BioContainers]]></title>
	<description><![CDATA[<p><span>BioContainers is a community-driven project that provides the infrastructure and basic guidelines to create, manage and distribute bioinformatics packages (e.g conda) and containers (e.g docker, singularity). BioContainers is based on the popular frameworks&nbsp;</span><a href="https://conda.io/">Conda</a><span>,&nbsp;</span><a href="https://www.docker.com/">Docker</a><span>&nbsp;and&nbsp;</span><a href="https://www.sylabs.io/docs/">Singularity</a><span>.</span></p><p>Address of the bookmark: <a href="https://biocontainers.pro/#/" rel="nofollow">https://biocontainers.pro/#/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/924/try-r-online</guid>
	<pubDate>Tue, 16 Jul 2013 06:15:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/924/try-r-online</link>
	<title><![CDATA[Try R Online]]></title>
	<description><![CDATA[<p>One of the best R tutorial website, which provide an online interative interface to try and learn R language without any hassle.</p><p>Link @ http://tryr.codeschool.com/</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3046/r-and-bioconductor-tutorial</guid>
	<pubDate>Fri, 23 Aug 2013 08:23:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3046/r-and-bioconductor-tutorial</link>
	<title><![CDATA[R and Bioconductor Tutorial]]></title>
	<description><![CDATA[<p>This tutorial is intended to introduce users quickly to the basics of R, focusing on a few common tasks that &nbsp;biologists need to perform &nbsp;some basic analysis: &nbsp;load a table, plot some graphs, and perform some basic statistics. More extensive tutorials can be found on the project website and via bioconductor (not covered here).</p>
<p>You can add more tutorial links in comments if found new pages.</p><p>Address of the bookmark: <a href="http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual" rel="nofollow">http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11030/r-programming-and-jobs-website</guid>
	<pubDate>Sun, 25 May 2014 14:43:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11030/r-programming-and-jobs-website</link>
	<title><![CDATA[R programming and Jobs website]]></title>
	<description><![CDATA[<p>Welcome to the R Jobs section of ProgrammingR.com. If your organization has an R employment opportunity that you would like to have posted here, submit it via the <a href="http://www.programmingr.com/contact" title="contact page">contact page</a>. Prospective employees: use the contact information provided in the position listing to apply or contact the hiring organization.</p><p>Address of the bookmark: <a href="http://www.programmingr.com/category/stype/r-job-listings/" rel="nofollow">http://www.programmingr.com/category/stype/r-job-listings/</a></p>]]></description>
	<dc:creator>Pragati Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19087/dcgor</guid>
	<pubDate>Sat, 08 Nov 2014 14:54:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19087/dcgor</link>
	<title><![CDATA[dcGOR]]></title>
	<description><![CDATA[<p>An R package for analysing ontologies and protein domain annotations has been published in PLoS Computational Biology (http://dx.doi.org/10.1371/journal.pcbi.1003929). The package is distributed as part of CRAN (http://cran.r-project.org/package=dcGOR), and also at GitHub for version control.<br /><br />The dedicated website is available in http://supfam.org/dcGOR, from which several demos are also provided:<br /><br />1. Analysing SCOP domains: http://supfam.org/dcGOR/demo-Fang.html<br /><br />2. Analysing Pfam domains: http://supfam.org/dcGOR/demo-Basu.html<br /><br />3. Analysing InterPro domains: http://supfam.org/dcGOR/demo-Customisation.html<br /><br />&nbsp;</p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21312/r-for-microsoft-excel</guid>
	<pubDate>Wed, 18 Feb 2015 00:43:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21312/r-for-microsoft-excel</link>
	<title><![CDATA[R for Microsoft Excel]]></title>
	<description><![CDATA[<div><p>If you currently use a spreadsheet like Microsoft Excel for data analysis, you might be interested in taking a look at this <a href="https://districtdatalabs.silvrback.com/intro-to-r-for-microsoft-excel-users" target="_blank">tutorial on how to transition from Excel to R</a>&nbsp;by Tony Ojeda. The tutorial explains how to use R functions in place of Excel formulas, including tools like =AVERAGE and =VLOOKUP. For the most part, it uses modern R packages to keep the R code clear and concise.</p><p>You'll likely still be using Excel as a data source, though, so you'll also want to check out this <a href="http://www.milanor.net/blog/?p=779" target="_blank">guide to importing data from Excel to R</a> from MilanoR.</p></div><p>Reference http://www.r-bloggers.com/an-r-tutorial-for-microsoft-excel-users/</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/21444/a-guide-for-complete-r-beginners-installing-r-packages</guid>
	<pubDate>Tue, 24 Feb 2015 20:23:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/21444/a-guide-for-complete-r-beginners-installing-r-packages</link>
	<title><![CDATA[A guide for complete R beginners :- Installing R packages]]></title>
	<description><![CDATA[<p>Part of the reason R has become so popular is the vast array of packages available at the <a href="http://cran.r-project.org/" target="_blank">cran</a> and <a href="http://www.bioconductor.org/" target="_blank">bioconductor</a> repositories. In the last few years, the number of packages has grown <a href="http://blog.revolutionanalytics.com/2010/09/what-can-other-languages-learn-from-r.html" target="_blank">exponentially</a>!</p><p>This is a short post giving steps on how to actually install R packages. Let&rsquo;s suppose you want to install the <a href="http://had.co.nz/ggplot2/" target="_blank">ggplot2</a> package. Well nothing could be easier. We just fire up an R shell and type:<br /><code><br />&gt; install.packages("ggplot2")</code></p><p>In theory the package should just install, however:</p><ul>
<li>if you are using Linux and don&rsquo;t have root access, this command won&rsquo;t work.</li>
<li>you will be asked to select your local mirror, i.e. which server should you use to download the package.</li>
</ul><h4>Installing packages without root access</h4><p>First, you need to designate a directory where you will store the downloaded packages. On my machine, I use the directory <code>/data/Rpackages/</code> After creating a package directory, to install a package we use the command:<br /><code><br />&gt; install.packages("ggplot2"</code><code>, lib="/data/Rpackages/")<br />&gt; library(ggplot2, lib.loc="/data/Rpackages/")<br /></code></p><p>It&rsquo;s a bit of a pain having to type <code>/data/Rpackages/</code> all the time. To avoid this burden,&nbsp; we create a file <code>.Renviron</code> in our home area, and add the line <code>R_LIBS=/data/Rpackages/</code> to it. This means that whenever you start R, the directory <code>/data/Rpackages/</code> is added to the list of places to look for R packages and so:</p><p><code>&gt; install.packages("ggplot2"</code><code>)<br />&gt; library(ggplot2)</code></p><p>just works!</p><h4>Setting the repository</h4><p>Every time you install a R package, you are asked which repository R should use. To set the repository and avoid having to specify this at every package install, simply:</p><ul>
<li>create a file <code>.Rprofile</code> in your home area.</li>
<li>Add the following piece of code to it:</li>
</ul><p><code><br />cat(".Rprofile: Setting UK repositoryn")<br />r = getOption("repos") # hard code the UK repo for CRAN<br />r["CRAN"] = "http://cran.uk.r-project.org"<br />options(repos = r)<br />rm(r)<br /></code></p><p>I found this tip in a stackoverflow <a href="http://stackoverflow.com/questions/1189759/expert-r-users-whats-in-your-rprofile/1189826#1189826" target="_blank">answer </a>.</p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
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