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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29635?offset=520</link>
	<atom:link href="https://bioinformaticsonline.com/related/29635?offset=520" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38385/decipher-a-software-toolset-for-deciphering-and-managing-biological-sequences-efficiently-using-the-r</guid>
	<pubDate>Sun, 09 Dec 2018 19:06:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38385/decipher-a-software-toolset-for-deciphering-and-managing-biological-sequences-efficiently-using-the-r</link>
	<title><![CDATA[DECIPHER; a software toolset for deciphering and managing biological sequences efficiently using the R]]></title>
	<description><![CDATA[<p><span>DECIPHER is a software toolset that can be used for deciphering and managing biological sequences efficiently using the&nbsp;</span><a href="http://www.r-project.org/">R</a><span>&nbsp;programming language. The&nbsp;</span><a href="http://www.r-project.org/">R</a><span>&nbsp;package is distributed as platform independent source code under the&nbsp;</span><a href="http://www.gnu.org/copyleft/gpl.html">GPL version 3 license</a><span>. Some functionality of the program is accessible online through web tools.</span></p>
<p><span style="font-size: medium; text-align: justify;">&nbsp;</span></p><p>Address of the bookmark: <a href="http://www2.decipher.codes/" rel="nofollow">http://www2.decipher.codes/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/12943/a-history-of-bioinformatics-in-the-year-2039</guid>
	<pubDate>Wed, 23 Jul 2014 06:37:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/12943/a-history-of-bioinformatics-in-the-year-2039</link>
	<title><![CDATA[A History of Bioinformatics (in the Year 2039)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/uwsjwMO-TEA" frameborder="0" allowfullscreen></iframe><p>C. Titus Brown http://video.open-bio.org/video/1/a-history-of-bioinformatics-in-the-year-2039</p>]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39114/plumberan-r-package-that-converts-your-existing-r-code-to-a-web-api</guid>
	<pubDate>Wed, 13 Mar 2019 19:20:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39114/plumberan-r-package-that-converts-your-existing-r-code-to-a-web-api</link>
	<title><![CDATA[plumber:An R package that converts your existing R code to a web API]]></title>
	<description><![CDATA[<p>plumber allows you to create a REST API by merely decorating your existing R source code with special comments. Take a look at an example.</p>
<pre><code><span># plumber.R
</span><span>
</span><span>#* Echo back the input
#* @param msg The message to echo
#* @get /echo
</span><span>function</span><span>(</span><span>msg</span><span>=</span><span>""</span><span>){</span><span>
  </span><span>list</span><span>(</span><span>msg</span><span> </span><span>=</span><span> </span><span>paste0</span><span>(</span><span>"The message is: '"</span><span>,</span><span> </span><span>msg</span><span>,</span><span> </span><span>"'"</span><span>))</span><span>
</span><span>}</span><span>

</span><span>#* Plot a histogram
#* @png
#* @get /plot
</span><span>function</span><span>(){</span><span>
  </span><span>rand</span><span> </span><span>&lt;-</span><span> </span><span>rnorm</span><span>(</span><span>100</span><span>)</span><span>
  </span><span>hist</span><span>(</span><span>rand</span><span>)</span><span>
</span><span>}</span><span>

</span><span>#* Return the sum of two numbers
#* @param a The first number to add
#* @param b The second number to add
#* @post /sum
</span><span>function</span><span>(</span><span>a</span><span>,</span><span> </span><span>b</span><span>){</span><span>
  </span><span>as.numeric</span><span>(</span><span>a</span><span>)</span><span> </span><span>+</span><span> </span><span>as.numeric</span><span>(</span><span>b</span><span>)</span><span>
</span><span>}</span></code></pre><p>Address of the bookmark: <a href="https://www.rplumber.io/" rel="nofollow">https://www.rplumber.io/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/11144/scientists-map-17294-proteins-produced-in-human-body</guid>
	<pubDate>Thu, 29 May 2014 01:57:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/11144/scientists-map-17294-proteins-produced-in-human-body</link>
	<title><![CDATA[Scientists map 17,294 proteins produced in human body]]></title>
	<description><![CDATA[<p>Indian scientists missed the genomic profiling bus, but they've more than made up for it by creating the first human proteome map which is an extension of the genomic study. Till now, here is no direct equivalent for the human proteome. But recently two groups present mass spectrometry-based analysis of human tissues, body fluids and cells mapping the large majority of the human proteome.</p><p>The Indian scientists working in Bangalore, along with their American counterparts, have mapped more than 17,000 proteins in 30 organs of the human body. Just like the human genome was sequenced around the turn of the millennium, this is an equivalent mapping of the human proteome.<br /><br />The researcher estimated there are around 20,500 proteins in the human body. These scientists have profiled around 17,294, which account for around 84% of the total proteins. Apart from this, the team also traced around 2,500 of 3,000 proteins that had been categorised as "missing proteins".</p><p>The work, done by group of Indian scientists, and Johns Hopkins University, published in the renowned journal Nature ( http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html ). Of the 72 people who worked on the project, 46 are Indians.</p><p>Reference:</p><p>http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html</p><p>http://www.proteinatlas.org/ -The antibody-based Human Protein Atlas programme</p><p>http://www.humanproteomemap.org/ -Proteogenomic analysis by identifying translated proteins from annotated pseudogenes, non-coding RNAs and untranslated regions.</p><p>https://www.proteomicsdb.org/ -Assembled protein evidence for 18,097 genes in ProteomicsDB</p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39947/radar-charts-with-ggplot2</guid>
	<pubDate>Tue, 17 Sep 2019 23:01:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39947/radar-charts-with-ggplot2</link>
	<title><![CDATA[radar charts with ggplot2]]></title>
	<description><![CDATA[<p><code>ggradar</code>&nbsp;allows you to build radar charts with ggplot2. This package is based on&nbsp;<a href="http://rstudio-pubs-static.s3.amazonaws.com/5795_e6e6411731bb4f1b9cc7eb49499c2082.html">Paul Williamson&rsquo;s</a>&nbsp;code, with new aesthetics and compatibility with ggplot2 2.0.</p>
<p>It was inspired by&nbsp;<a href="http://www.buildingwidgets.com/blog/2015/12/9/week-49-d3radarr">d3radaR</a>, an htmlwidget built by&nbsp;<a href="https://github.com/timelyportfolio">timelyportfolio</a>.</p><p>Address of the bookmark: <a href="https://github.com/ricardo-bion/ggradar" rel="nofollow">https://github.com/ricardo-bion/ggradar</a></p>]]></description>
	<dc:creator>Rahul Nayak</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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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</guid>
	<pubDate>Sun, 01 Jun 2014 23:38:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</link>
	<title><![CDATA[Genomics and Personalized Medicine]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/pgHAXCMMcro" frameborder="0" allowfullscreen></iframe>(October 20, 2009) Michael Snyder, Professor of Genetics and Chair of the Department of Genetics at Stanford, discusses advances in gene sequencing, the impact of genomics on medicine, the potential for personalized medicine. and efforts at Stanford to further study these issues.

Stanford Mini Med School is a series arranged and directed by Stanford's School of Medicine, and presented by the Stanford Continuing Studies program. Featuring more than thirty distinguished, faculty, scientists and physicians from Stanford's medical school, the series offers students a dynamic introduction to the world of human biology, health and disease, and the groundbreaking changes taking place in medical research and health care.

Stanford University
http://www.stanford.edu

Stanford University School of Medicine
http://med.stanford.edu

Stanford Continuing Studies
http://continuingstudies.stanford.edu

Stanford University Channel on YouTube:
http://www.youtube.com/stanford]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41272/rainbowr-reliable-association-inference-by-optimizing-weights-with-r-r-package-for-snp-set-gwas-and-multi-kernel-mixed-model</guid>
	<pubDate>Fri, 28 Feb 2020 23:27:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41272/rainbowr-reliable-association-inference-by-optimizing-weights-with-r-r-package-for-snp-set-gwas-and-multi-kernel-mixed-model</link>
	<title><![CDATA[RAINBOWR: Reliable Association INference By Optimizing Weights with R (R package for SNP-set GWAS and multi-kernel mixed model)]]></title>
	<description><![CDATA[<p><code>RAINBOWR</code>(Reliable Association INference By Optimizing Weights with R) is a package to perform several types of <code>GWAS</code> as follows.</p>
<ul>
<li>Single-SNP GWAS with <code>RGWAS.normal</code> function</li>
<li>SNP-set (or gene set) GWAS with <code>RGWAS.multisnp</code> function (which tests multiple SNPs at the same time)</li>
<li>Check epistatic (SNP-set x SNP-set interaction) effects with <code>RGWAS.epistasis</code> (very slow and less reliable)</li>
</ul>
<p>https://github.com/KosukeHamazaki/RAINBOWR</p>
<p>https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007663</p>
<p>https://cran.r-project.org/web/packages/RAINBOWR/index.html</p><p>Address of the bookmark: <a href="https://github.com/KosukeHamazaki/RAINBOWR" rel="nofollow">https://github.com/KosukeHamazaki/RAINBOWR</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11434/adhoc-bioinformatics-faculty-position-nit</guid>
  <pubDate>Tue, 03 Jun 2014 16:19:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Adhoc Bioinformatics Faculty Position @ NIT]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF TECHNOLOGY, DEPARTMENT OF BIOTECHNOLOGY, WARANGAL – 506 021, Andhra Pradesh</p>

<p>No.NITW/BT/2014/adhoc</p>

<p>APPLICATIONS ARE INVITED FOR THE APPOINTMENT OF ADHOC FACULTY ON CONTRACT BASIS IN THE DEAPARTMENT OF BIOTECHNOLOGY</p>

<p>Period of Contract: Initially the appointment is for one semester i.e., from July 2014 up to December 2014 only.</p>

<p>Essential Qualifications:</p>

<p>i) B. Tech or equivalent in Biotechnology/ Industrial Biotechnology/ Biochemical Engineering / Chemical Engg. Or M. Sc in Microbiology/ Botany/ Zoology/ Biochemistry/Biotechnology and ii) M. Tech or equivalent in Biotechnology/Industrial Biotechnology/Bioinformatics</p>

<p>Or</p>

<p>Integrated M. Tech in Biotechnology/Industrial Biotechnology/ Bioinformatics</p>

<p>Candidates must possess First class (60% aggregate marks or 6.5 CGPA) at B. Tech/ M. Sc and M. Tech.</p>

<p>Desirable: Ph. D Pay Package: All selected candidates shall be eligible for a consolidated pay of Rs.30, 000/- per month. Candidates with Ph. D shall be eligible for an additional amount of Rs.5, 000/- per month.</p>

<p>How to apply : Applications on plain paper with attested photocopies of certificate and bio data along with justification for eligibility should reach to the Head, Department of Biotechnology, National Institute of Technology, Warangal AP 506004 in the form of soft or hard copy on or before 21st June 2014 email : biotech_hod@nitw.ac.in</p>

<p>Intimation: No separate call letters will be sent to the candidates. All the eligible candidates will be notified in the institute web site on 23rd June 2014. All the eligible candidates are requested to report for the interview to the Head, Department of Biotechnology at 9:00 AM on 27th June 2014</p>

<p>Joining: Selected candidates will be informed and they are expected to join immediately.</p>

<p>Advertisement:</p>

<p>http://www.nitw.ac.in/nitw/announcements/2014/Bio-Adhoc%20Advt.%20May-2014.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42299/platypus-%E2%80%93-r-package-for-object-detection-and-image-segmentation</guid>
	<pubDate>Mon, 09 Nov 2020 02:56:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42299/platypus-%E2%80%93-r-package-for-object-detection-and-image-segmentation</link>
	<title><![CDATA[Platypus – R package for object detection and image segmentation.]]></title>
	<description><![CDATA[<p><a href="https://github.com/maju116/platypus" target="_blank">platypus</a>&nbsp;is an R package for object detection and semantic segmentation. Currently using&nbsp;</p>
<div>platypus&nbsp;you can perform:</div>
<ul>
<li>multi-class semantic segmentation using&nbsp;U-Net&nbsp;architecture</li>
<li>multi-class object detection using&nbsp;YOLOv3&nbsp;architecture</li>
</ul>
<p>You can install the latest version of&nbsp;platypus&nbsp;with&nbsp;remotes&nbsp;package:</p>
<div>
<div>
<div>
<div>remotes::install_github("maju116/platypus")</div>
</div>
</div>
</div>
<p>Note that in order to install&nbsp;platypus&nbsp;you need to install&nbsp;keras&nbsp;and&nbsp;tensorflow&nbsp;packages and&nbsp;Tensorflow&nbsp;version&nbsp;&gt;= 2.0.0&nbsp;(&nbsp;Tensorflow 1.x&nbsp;will not be supported!)</p><p>Address of the bookmark: <a href="https://github.com/maju116/platypus" rel="nofollow">https://github.com/maju116/platypus</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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