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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/21443?offset=1130</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/38226/ncbi-to-assist-in-virus-hunting-data-science-hackathon</guid>
	<pubDate>Thu, 15 Nov 2018 12:55:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/38226/ncbi-to-assist-in-virus-hunting-data-science-hackathon</link>
	<title><![CDATA[NCBI to assist in Virus Hunting Data Science Hackathon]]></title>
	<description><![CDATA[<p>NCBI Hackathon are pleased to announce the second installment of the&nbsp;<a href="https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/30/ncbi-southern-california-genomics-hackathon-january/" target="_blank">SoCal Bioinformatics Hackathon</a>. From January 9-11, 2019, the&nbsp;<a href="https://www.ncbi.nlm.nih.gov/" target="_blank">NCBI</a>&nbsp;will help run a bioinformatics hackathon in Southern California hosted by the&nbsp;<a href="http://www.csrc.sdsu.edu/" target="_blank">Computational Sciences Research Center</a>&nbsp;at&nbsp;<a href="http://www.sdsu.edu/" target="_blank">San Diego State University</a>!</p><p><span>NCBI Hackathon</span>&nbsp;specifically looking for folks who have experience in computational virus hunting or adjacent fields to identify known, taxonomically-definable and novel viruses from a few hundred thousand metagenomic datasets that we&rsquo;ll put on cloud infrastructure. This event is for researchers, including students and postdocs, who are already engaged in the use of bioinformatics data or in the development of pipelines for virological analyses from high-throughput experiments. If this describes you, please&nbsp;<a href="https://goo.gl/forms/kDnSG0IAZD62XQRe2" target="_blank">apply</a>! The event is open to anyone selected for the hackathon and willing to travel to SDSU (see below).</p><p>https://ncbiinsights.ncbi.nlm.nih.gov/2018/11/09/ncbi-sdsu-virus-hunting-data-science-hackathon-january-2019/</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</guid>
	<pubDate>Mon, 20 Jan 2020 05:13:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</link>
	<title><![CDATA[De novo Genome Assembly for Illumina Data]]></title>
	<description><![CDATA[<p>Written and maintained by <a href="mailto:simon.gladman@unimelb.edu.au">Simon Gladman</a> - Melbourne Bioinformatics (formerly VLSCI)</p>
<p>Protocol Overview / Introduction</p>
<p>In this protocol we discuss and outline the process of de novo assembly for small to medium sized genomes.</p>
<p>https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</p><p>Address of the bookmark: <a href="https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/" rel="nofollow">https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42419/biojupies-automatically-generates-rna-seq-data-analysis-notebooks</guid>
	<pubDate>Sun, 20 Dec 2020 11:43:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42419/biojupies-automatically-generates-rna-seq-data-analysis-notebooks</link>
	<title><![CDATA[BioJupies: Automatically Generates RNA-seq Data Analysis Notebooks]]></title>
	<description><![CDATA[<p>With BioJupies you can produce in seconds a customized, reusable, and interactive report from your own raw or processed RNA-seq data through a simple user interface</p>
<p>BioJupies now supports user accounts! Sign in from the top right corner of the page for access to unlimited private notebooks, RNA-seq datasets and alignment jobs.</p><p>Address of the bookmark: <a href="https://amp.pharm.mssm.edu/biojupies/" rel="nofollow">https://amp.pharm.mssm.edu/biojupies/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44557/fundamentals-of-data-visualization-by-claus-o-wilke</guid>
	<pubDate>Sat, 08 Jun 2024 16:07:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44557/fundamentals-of-data-visualization-by-claus-o-wilke</link>
	<title><![CDATA[Fundamentals of Data Visualization by Claus O. Wilke]]></title>
	<description><![CDATA[<p><span><span>The book is meant as a guide to making visualizations that accurately reflect the data, tell a story, and look professional. It has grown out of my experience of working with students and postdocs in my laboratory on thousands of data visualizations. Over the years, I have noticed that the same issues arise over and over. I have attempted to collect my accumulated knowledge from these interactions in the form of this book.</span></span></p>
<p><span>The entire book is written in R Markdown, using RStudio as my text editor and the&nbsp;</span><span>bookdown</span><span>&nbsp;package to turn a collection of markdown documents into a coherent whole. The book&rsquo;s source code is hosted on GitHub, at&nbsp;</span><a href="https://github.com/clauswilke/dataviz">https://github.com/clauswilke/dataviz</a><span>.&nbsp;</span></p><p>Address of the bookmark: <a href="https://clauswilke.com/dataviz/" rel="nofollow">https://clauswilke.com/dataviz/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/view/119</guid>
	<pubDate>Wed, 10 Jul 2013 14:35:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/119</link>
	<title><![CDATA[Which are the best statistical programming languages to study for a bioinformatician?]]></title>
	<description><![CDATA[<p><span>In Bio-informatics based&nbsp;genome sequencing and predicting metabolic pathways&nbsp;research jobs&nbsp;I used Matlab, SAS, SPSS, R and several Bioconductor packages. Matlab had a lot of powerful tools and was easy to use, whereas SPSS is for non-programmers and R need programming skills. I am wondering what other people think is best? or there might not be one specific language but a few that lend themselves best to Bio-informatics work that is math heavy and deals with a large amount of data.</span></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4433/upcoming-r-webinar</guid>
	<pubDate>Wed, 11 Sep 2013 10:30:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4433/upcoming-r-webinar</link>
	<title><![CDATA[Upcoming R Webinar]]></title>
	<description><![CDATA[<p>This webinar will describe an R based approach to considerably speed GWAS computation time on a notebook book computer.</p><p>More http://www.extension.org/pages/68354/upcoming-webinar:-fast-semi-parallel-linear-and-logistic-regression-for-genome-wide-association-studi#.UjCL9azyPqV</p><p>Register @ https://www1.gotomeeting.com/register/237810425</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17504/postdoc-scientist-bioinformatics-at-ccmb</guid>
  <pubDate>Fri, 26 Sep 2014 19:58:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[PostDoc Scientist Bioinformatics at CCMB]]></title>
  <description><![CDATA[
<p>1. Project Assistant/Junior Research Fellow/ Project Fellow [PA_JRF_PF]</p>

<p>a) M.Sc/or equivalent in biological sciences/related areas [Position Code: PA_JRF_PF_a]<br />b) B.E/B.Tech/ M.Sc in biotechnology/bioinformatics/computer science/Chemistry/Physics or MCA [Position Code: PA_JRF_PF_b]<br />c) M.Sc/or equivalent in wildlife sciences/ecology/environmental sciences or MBBS/BVSc/MVSc. [Position Code: PA_JRF_PF_c]</p>

<p>(Candidates with result awaited are NOT eligible to apply)</p>

<p>Upper Age limit 28years</p>

<p>Rs.12000 / Rs.16000 (as sanctioned by the funding agency)</p>

<p>2. Post Doctoral Fellow/Research Associate in multiple research areas [PDF_RA]</p>

<p>Ph.D. (submitted/awarded) in any branch of biological Sciences. Candidates with Ph.D. in other sciences are also encouraged to apply.</p>

<p>Experience in molecular biology, biochemistry, structural biology, cell biology, infectious disease, conservation genetics, veterinary science, reproductive biology, and molecular diagnostics is desired but not mandatory.</p>

<p>[Position Code: PDF_RA]</p>

<p>UpperAge limit 35years</p>

<p>Rs. 22000- 26000 (as sanctioned by the funding agency)</p>

<p>3. Post Doctoral Scientist Fellow [PDSF]</p>

<p>Ph.D in any of the following areas: bioinformatics, next generation sequencing, high throughput data analysis, proteomics, bio-statistics, computer science, information technology, computer hardware and networking/clustering, parallel processing.<br />[Position Code: PDSF]</p>

<p>Upper Age limit 40 years</p>

<p>Rs. 40000 consolidated (as sanctioned by the funding agency)</p>

<p>Download Application: Last date for apply online: 09th Oct 2014</p>

<p>Advertisement: www.ccmb.res.in//index.php?view=notifications&amp;mid=0&amp;id=71&amp;nid=38</p>

<p>Apply online http://www.ccmb.res.in/positions/temp_notif/online_form.html</p>

<p>More at http://www.ccmb.res.in//index.php?view=notifications&amp;mid=0&amp;id=71&amp;nid=38</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34041/r-tuorial</guid>
	<pubDate>Mon, 31 Jul 2017 08:41:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34041/r-tuorial</link>
	<title><![CDATA[R tuorial]]></title>
	<description><![CDATA[<p>R learning resources</p>
<p>https://flowingdata.com/</p><p>Address of the bookmark: <a href="https://flowingdata.com/" rel="nofollow">https://flowingdata.com/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/17652/arraygen-bioinformatics-genomics-group</guid>
  <pubDate>Sun, 28 Sep 2014 14:09:55 -0500</pubDate>
  <link></link>
  <title><![CDATA[ArrayGen Bioinformatics Genomics Group]]></title>
  <description><![CDATA[
<p>ArrayGen is a global bioinformatics company which is a one stop solution for microarray designing and genomics data analysis. Our novel Array Design Approach Strategy (ADAS) aims to condense the time lag between demands of scientific community and manufacture industry, thereby expediting research processes.</p>

<p>ArrayGen specializes in Genomics data analysis and research, as we believe in the level of precision, predictability, benchmark-ability, and data analysis capability of genomics data over other forms of biological data. ArrayGen constantly strives to develop new solutions, and plug the existing gaps in the technological advancement of the field.</p>

<p>More http://www.arraygen.com/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r</guid>
	<pubDate>Fri, 06 Apr 2018 12:10:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r</link>
	<title><![CDATA[d3Network:Tools for creating D3 JavaScript network, tree, dendrogram, and Sankey graphs from R.]]></title>
	<description><![CDATA[<p><a href="http://bost.ocks.org/mike/">Mike Bostock</a><span>&rsquo;s&nbsp;</span><a href="http://d3js.org/">D3.js</a><span>&nbsp;is great for creating&nbsp;</span><a href="http://bl.ocks.org/mbostock/4062045">interactive network graphs</a><span>&nbsp;with JavaScript. The&nbsp;</span><a href="https://github.com/christophergandrud/d3Network">d3Network</a><span>&nbsp;package makes it easy to create these network graphs from&nbsp;</span><a href="http://www.r-project.org/">R</a><span>. The main idea is that you should able to take an R data frame with information about the relationships between members of a network and create full network graphs with one command.</span></p><p>Address of the bookmark: <a href="http://christophergandrud.github.io/d3Network/" rel="nofollow">http://christophergandrud.github.io/d3Network/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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