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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28884?offset=1210</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</guid>
	<pubDate>Sun, 12 Apr 2020 10:02:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</link>
	<title><![CDATA[WEGO : simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results]]></title>
	<description><![CDATA[<p><span>WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary became more and more popular, WEGO was widely adopted and used in many researches. Therefore we have updated WEGO 2.0 in 2018. Here are some changes we&rsquo;ve made:</span><br><span>1. The limit of input file numbers was cancelled. Now the users could upload as many files as they want with one operation.</span><br><span>2. We have added the reference data of 9 species for users selection.</span><br><span>3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.</span></p><p>Address of the bookmark: <a href="http://wego.genomics.org.cn/" rel="nofollow">http://wego.genomics.org.cn/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21095/ra-walk-in-interview-actrec</guid>
  <pubDate>Mon, 09 Feb 2015 01:06:16 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA WALK-IN-INTERVIEW @ ACTREC]]></title>
  <description><![CDATA[
<p>No. ACTREC/Advt./ 7 /2015</p>

<p>Title of the Project<br />Research Associate<br />(One position)<br />DBTs Biotechnology/Bioinformatics training centre<br />PI Dr. Ashok Varma	</p>

<p>Duration of the Project Six Months from the date of appointment, can be extended further for six month.</p>

<p>Date &amp; Time: 17th February, 2015 at 10.00 a.m.</p>

<p>Venue: Meeting Room, 3rd floor, Khanolkar Shodhika, ACTREC</p>

<p>Essential Qualifications and Experience:</p>

<p>Ph.D. Degree in Basic Sciences from recognized University. Research experience in Bioinformatics or on gene cloning, protein purification, and crystallization.</p>

<p>*M.Sc. degree obtained after a one year course will not be considered.</p>

<p>Selected candidate will have to join at the earliest.</p>

<p>Consolidated Salary: Rs.28,600/- p.m. {Rs.22,000/- + 30% HRA}</p>

<p>The work progress of the candidate will be monitored and extension after 6 months will depend on satisfactory progress of the work.</p>

<p>Candidates fulfilling these requirements should pre-register by sending their application in the prescribed format with recent CV and contact details of 2 referees by e-mail to ‘program.office@actrec.gov.in’ latest by 17.00 hrs on 12-02-2015.<br />The interviews would be held on 17th February, 2015 and will be only for the pre-registered candidates. Candidates should report between 09.30 to 10.00 a.m. in Steno Pool, 3rd floor, Khanolkar Shodhika, ACTREC, Kharghar, Navi Mumbai.<br />No T.A./D.A. will be admissible for attending the interview.</p>

<p>At the time of Interview the candidate should bring original certificates along with CV with contact details of 2 referees and submit the photocopies (attested) of the certificates, with a recent passport size photograph.</p>

<p>All correspondence should be strictly made only to ‘program.office@actrec.gov.in’ as indicated.</p>

<p>Advertisement: www.actrec.gov.in/data%20files/2015/AV-RA-DBT-28-1-15.docx</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40991/jtools-more-efficient-presentation-of-regression-analyses</guid>
	<pubDate>Tue, 11 Feb 2020 23:10:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40991/jtools-more-efficient-presentation-of-regression-analyses</link>
	<title><![CDATA[jtools : more efficient presentation of regression analyses]]></title>
	<description><![CDATA[<p>This package consists of a series of functions created by the author (Jacob) to automate otherwise tedious research tasks. At this juncture, the unifying theme is the more efficient presentation of regression analyses. There are a number of functions for other programming and statistical purposes as well. Support for the&nbsp;<code>survey</code>&nbsp;package&rsquo;s&nbsp;<code>svyglm</code>&nbsp;objects as well as weighted regressions is a common theme throughout.</p>
<p><strong>Notice:</strong>&nbsp;As of&nbsp;<code>jtools</code>&nbsp;version 2.0.0, all functions dealing with interactions (e.g.,&nbsp;<code>interact_plot()</code>,&nbsp;<code>sim_slopes()</code>,&nbsp;<code>johnson_neyman()</code>) have been moved to a new package, aptly named&nbsp;<a href="https://interactions.jacob-long.com/"><code>interactions</code></a>.</p><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/jtools/readme/README.html" rel="nofollow">https://cran.r-project.org/web/packages/jtools/readme/README.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21242/summer-intern-research-bioinformatics</guid>
  <pubDate>Mon, 16 Feb 2015 12:26:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[Summer Intern - Research Bioinformatics]]></title>
  <description><![CDATA[
<p>Be proficient in LINUX, know perl or python, understand biology and Next Generation Sequencing.<br />The intern will port Agile Assay Design pipelines into Galaxy.<br />The intern will also learn to develope his/her own bioinformatics pipelines for PCR or NGS data analysis.</p>

<p>Who you are<br />You’re someone who wants to influence your own development. You’re looking for a company where you have the opportunity to pursue your interests across functions and geographies. Where a job title is not considered the final definition of who you are, but the starting point.</p>

<p>Qualifications:<br />Major: Bioinformatcis or biology major who is interested and wants to learn Biocomputing, At least 2 years of college.<br />Basic knowledge of LINUX and programming, e.g., perl, python, XML.</p>

<p>More at http://www.roche.com/careers/jobs/jobsearch/job.htm?id=E-00437679&amp;locale=en&amp;title=Summer%20Intern%20-%20Research%20Bioinformatics</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44208/circos-visualization</guid>
	<pubDate>Mon, 06 Mar 2023 06:01:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44208/circos-visualization</link>
	<title><![CDATA[Circos visualization !]]></title>
	<description><![CDATA[<p>Circos visualization</p>
<p>https://wlcb.oit.uci.edu/modules/index.html</p><p>Address of the bookmark: <a href="https://wlcb.oit.uci.edu/NG-Circos" rel="nofollow">https://wlcb.oit.uci.edu/NG-Circos</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21436/jrf-bioinformatics-iisr-kozhikode</guid>
  <pubDate>Tue, 24 Feb 2015 08:44:17 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics @ IISR, Kozhikode]]></title>
  <description><![CDATA[
<p>JRF Bioinformatics Jobs recruitment in Indian Institute of Spices Research on temporary basis</p>

<p>Name of the Scheme : Distributed Information Sub Centre – DISC</p>

<p>Qualifications :  M.Sc/ B Tech in Bioinformatics with NET/GATE or M Tech in Bioinformatics</p>

<p>Number of posts : One</p>

<p>Emoluments : Rs. 25,000/-</p>

<p>Upper age limit : 35 years for Men &amp; 40 years for Women as on date of Interview<br />How to apply</p>

<p>Date of Interview : 12-03-2015 at 10.00 AM. All relevant certificates (in original) and bio data, No objection certificate in case he/she is employed elsewhere and experience certificate in original (if any) need to be produced at the time of interview.</p>

<p>More at http://spices.res.in/index.php?option=com_content&amp;view=article&amp;id=263</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37460/revigo-reduced-visualize-gene-ontology</guid>
	<pubDate>Tue, 31 Jul 2018 05:28:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37460/revigo-reduced-visualize-gene-ontology</link>
	<title><![CDATA[REVIGO: Reduced Visualize gene ontology]]></title>
	<description><![CDATA[<div>REViGO can take long lists of Gene Ontology terms and summarize them by removing redundant GO terms. The remaining terms can be visualized in semantic similarity-based scatterplots, interactive graphs, or tag clouds.&nbsp;<a href="http://dx.doi.org/10.1371/journal.pone.0021800">More about REViGO...</a>&nbsp;|&nbsp;<a href="http://revigo.irb.hr/about_hr.jsp"><img src="http://revigo.irb.hr/gfx/croatian-wCrown.png" alt="In Croatian" title="" width="12" height="15" style="border: 0px;"></a></div>
<div>Please enter a list of Gene Ontology IDs below, each on its own line. The GO IDs may be followed by p-values or another quantity which describes the GO term in a way meaningful to you.&nbsp;<img src="http://revigo.irb.hr/gfx/qmark.png" alt="For instance, you may provide a p-value          (statistical significance), a fold change, enrichment, or some          directly measured quantity such as average signal intensity from          microarrays, ion count from mass spec, or read count from RNA-seq.          You may also provide more than one value per line, although only the          first value will be used in GO term selection/clustering." title="" width="16" height="15" style="border: 0px;"></div><p>Address of the bookmark: <a href="http://revigo.irb.hr/" rel="nofollow">http://revigo.irb.hr/</a></p>]]></description>
	<dc:creator>Jit</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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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40583/trelliscope-flexibly-visualize-large-complex-data-in-great-detail-from-within-the-r-statistical-programming-environment</guid>
	<pubDate>Tue, 21 Jan 2020 04:22:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40583/trelliscope-flexibly-visualize-large-complex-data-in-great-detail-from-within-the-r-statistical-programming-environment</link>
	<title><![CDATA[Trelliscope: flexibly visualize large, complex data in great detail from within the R statistical programming environment.]]></title>
	<description><![CDATA[<p>Trelliscope provides a way to flexibly visualize large, complex data in great detail from within the R statistical programming environment. Trelliscope is a component in the<span>&nbsp;</span><a href="http://deltarho.org/docs-trelliscope/deltarho.org">DeltaRho</a><span>&nbsp;</span>environment.</p>
<p>For those familiar with<span>&nbsp;</span><a href="http://cm.bell-labs.com/cm/ms/departments/sia/project/trellis/">Trellis Display</a>,<span>&nbsp;</span><a href="http://docs.ggplot2.org/0.9.3.1/facet_wrap.html">faceting in ggplot</a>, or the notion of<span>&nbsp;</span><a href="http://en.wikipedia.org/wiki/Small_multiple">small multiples</a>, Trelliscope provides a scalable way to break a set of data into pieces, apply a plot method to each piece, and then arrange those plots in a grid and interactively sort, filter, and query panels of the display based on metrics of interest. With Trelliscope, we are able to create multipanel displays on data with a very large number of subsets and view them in an interactive and meaningful way.</p><p>Address of the bookmark: <a href="http://deltarho.org/docs-trelliscope/#introduction" rel="nofollow">http://deltarho.org/docs-trelliscope/#introduction</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21830/research-associate-bioinformatics-job-position-in-indian-agricultural-statistics-research-institute-iasri</guid>
  <pubDate>Tue, 31 Mar 2015 20:45:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate Bioinformatics job position in Indian Agricultural Statistics Research Institute (IASRI)]]></title>
  <description><![CDATA[
<p>Research Associate Bioinformatics job position in Indian Agricultural Statistics Research Institute (IASRI)</p>

<p>Qualification : Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent. Desirable: Knowledge of Statistical and Computational Genomics/ Proteomics/ Bioinformatics OR Post-Graduation in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent with 1st Division or 60% marks or equivalent with at least two years of research experience. Desirable:Expertise on use of various software/ tool.</p>

<p>No.of Post: 2</p>

<p>Emoluments for RA: Consolidated Rs. 24000/- per month + 30% HRA for Ph.D holders and consolidated Rs. 23000/- per month + 30% HRA for Master Degree.</p>

<p>Age Limit : Age should not be more than 40 years for the post of Research associate (5 years relaxation for SC/ST/ women candidates) and 3 years for OBC candidates as on date of interview.<br />How to apply</p>

<p>Interested candidates are invited to appear for Walk-In interview at Indian Agricultural Statistics Research Institute, Library Avenue, Pusa, New Delhi -110012, along with filled in application form , all the original certificates from matriculation onwards, Ph.D. or M.Sc. certificate (as the case may be) must be produced at the time of interview in either original or provisional, Bio-Data, attested copies of all experience certificates, testimonials etc., one passport size photograph and one set of the self-attested photocopies of all the required certificates from matriculation onwards and an attested copy of recent passport size photograph pasted onto the application form. Walk-in interview will be held on 16th April, 2015 at 10:30 a.m.</p>

<p>Click Here for Job Details &amp; Application Form http://www.iasri.res.in/employment/employment.htm</p>
]]></description>
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