<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/23892?offset=30</link>
	<atom:link href="https://bioinformaticsonline.com/related/23892?offset=30" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20440/linux-operating-system-aimed-at-scientists</guid>
	<pubDate>Mon, 19 Jan 2015 08:30:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20440/linux-operating-system-aimed-at-scientists</link>
	<title><![CDATA[Linux operating system aimed at scientists]]></title>
	<description><![CDATA[<p>The Bio-Linux operating system is based on Ubuntu 14.04 LTS (Trusty Tahr), and the previous version was using Ubuntu 12.04 LTS. The developers only use LTS releases and that means that upgrades for this distro don't come along all that often.<br /> <br /> This Linux distribution is aimed at scientists and it comes with more than 250 bioinformatics packages, 50 graphical applications and several hundred command line tools. And this is just skimming the surface of what the OS can do. Users have access to even more apps from the official repositories.</p><h3>Bio-Linux is using an Ubuntu LTS version as its base</h3><p>The fact that it uses Ubuntu LTS versions for the base is a good thing because it means its users won't have to worry about the support. Ubuntu 14.04 LTS is supported until 2019, so people who are using Bio-Linux shouldn't have a problem.<br /> <br /> "An updated Bio-Linux 8 version is now on the website in ISO and OVA versions. As usual, there is no need to download this version if you are an existing user. All updates to existing packages will be applied to your system through the update manager and new packages are all available via apt-get or Synaptic," reads the <a href="http://nebclists.nerc.ac.uk/pipermail/bio-linux-announce/2015-January/000020.html" target="_blank">announcement</a>.<br /> <br /> The changelog also states that a problem that was preventing the desktop to not start on VirtualBox has been fixed, the QIIME and Bowtie-Bio tools have been upgraded, the pandaseq paired end assembler has been added, and the beginners tutorial specific to Bio-Linux 8 has been improved.<br /> <br /> Check out the official announcement for a complete list of changes and updates. You can <a href="http://linux.softpedia.com/get/System/Operating-Systems/Linux-Distributions/Bio-Linux-45495.shtml" target="_blank"><strong>download Bio-Linux 8.0.5</strong></a> right now from Softpedia and give it a spin. It has the Unity desktop and now it runs very well in virtual environments.</p><p>Reference @ http://news.softpedia.com/news/Bioinformatics-Distro-Bio-Linux-8-0-5-Now-Available-for-Download-469867.shtml</p>]]></description>
	<dc:creator>Pranjali Yadav</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/20585/dna-transcription-advanced</guid>
	<pubDate>Thu, 29 Jan 2015 05:31:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/20585/dna-transcription-advanced</link>
	<title><![CDATA[DNA Transcription (Advanced)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/SMtWvDbfHLo" frameborder="0" allowfullscreen></iframe><p>Transcription is the process by which the information in DNA is copied into messenger RNA (mRNA) for protein production. Originally created for DNA Interactive ( http://www.dnai.org ). TRANSCRIPT: The Central Dogma of Molecular Biology: "DNA makes RNA makes protein" Here the process begins. Transcription factors assemble at a specific promoter region along the DNA. The length of DNA following the promoter is a gene and it contains the recipe for a protein. A mediator protein complex arrives carrying the enzyme RNA polymerase. It manoeuvres the RNA polymerase into place... inserting it with the help of other factors between the strands of the DNA double helix. The assembled collection of all these factors is referred to as the transcription initiation complex... and now it is ready to be activated. The initiation complex requires contact with activator proteins, which bind to specific sequences of DNA known as enhancer regions. These regions may be thousands of base pairs distant from the start of the gene. Contact between the activator proteins and the initiation-complex releases the copying mechanism. The RNA polymerase unzips a small portion of the DNA helix exposing the bases on each strand. Only one of the strands is copied. It acts as a template for the synthesis of an RNA molecule which is assembled one sub-unit at a time by matching the DNA letter code on the template strand. The sub-units can be seen here entering the enzyme through its intake hole and they are joined together to form the long messenger RNA chain snaking out of the top.</p>]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/21365/a-guide-for-complete-r-beginners</guid>
	<pubDate>Fri, 20 Feb 2015 23:36:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/21365/a-guide-for-complete-r-beginners</link>
	<title><![CDATA[A guide for complete R beginners !]]></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><em><span style="text-decoration: underline;">R-language: </span></em><a href="http://www.r-project.org/"><span style="color: #000080;"><span style="text-decoration: underline;"><em>http://www.</em></span></span><span style="color: #000080;"><span style="text-decoration: underline;"><em><strong>r</strong></em></span></span><span style="color: #000080;"><span style="text-decoration: underline;"><em>-project.org</em></span></span></a></p><p><em>BioConductor</em>:&nbsp;<a href="http://www.bioconductor.org/">http://www.bioconductor.org</a></p><p><strong>Advantages of R</strong></p><ul>
<li>Free!</li>
<li>Powerful, many libraries have been created to perform application specific tasks. e.g. analysis of microarray experiments and Next-Gen sequencing (bioconductor: including Bioseq group).</li>
<li>Presentation quality graphics
<ul>
<li>Save as a png, pdf or svg</li>
</ul>
</li>
<li>History
<ul>
<li>What you do can be saved for the next time you use R.</li>
<li>Ability to turn it into an automated script to perform again and again on different data</li>
</ul>
</li>
</ul><p><strong>Disadvantages</strong></p><ul>
<li>Lack of a comprehensive graphical user interface, but two do exist: However some do exist:&nbsp;R commander: <a href="http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/">http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/</a> and&nbsp;Limma-gui (microarrays) : <a href="http://bioinf.wehi.edu.au/limmaGUI/">http://bioinf.wehi.edu.au/limmaGUI/</a></li>
</ul><p><strong>Preparation</strong></p><ul>
<li>(Optional) Download and save the tutorial data set from
<ul>
<li>http://bioinformatics.knowledgeblog.org/wp-content/uploads/bioinf/kerr/data.tsv</li>
<li>Start R (type R on a Linux or Mac terminal, or find the starting link from PC)</li>
</ul>
</li>
</ul><p><strong>Getting More Help</strong></p><ul>
<li>Project Home page
<ul>
<li><span style="color: #000080;"><span style="text-decoration: underline;"><a href="http://www.r-project.org/">http://www.r-project.org/</a></span></span></li>
<li>Check out the &lsquo;introduction to R&rsquo;, which is a much more in depth guide .</li>
<li>Also R has a built-in help system (see later)</li>
</ul>
</li>
</ul><p><strong>Working directory</strong></p><p>This is the directory used to store your data and results. It is useful if it is also the directory where your input data is stored.</p><ul>
<li>Mac/Linux: this is the directory where you typed in R</li>
<li>PC: Change using the change working directory option</li>
</ul>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/22352/affy-has-acquired-eureka-genomics-for-15m</guid>
	<pubDate>Wed, 20 May 2015 15:11:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/22352/affy-has-acquired-eureka-genomics-for-15m</link>
	<title><![CDATA[Affy has acquired Eureka Genomics for 15M $]]></title>
	<description><![CDATA[<p>Affymetrix Acquires Assets Of Eureka Genomics Corporation To Provide High Throughput And Economical Crop And Animal Genotyping</p><p>http://www.thestreet.com/story/13151062/1/affymetrix-acquires-assets-of-eureka-genomics-corporation-to-provide-high-throughput-and-economical-crop-and-animal-genotyping.html</p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/22793/sequencing-by-xpansion</guid>
	<pubDate>Wed, 17 Jun 2015 20:58:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/22793/sequencing-by-xpansion</link>
	<title><![CDATA[Sequencing By Xpansion]]></title>
	<description><![CDATA[<p>Sequencing By Xpansion (SBX) is a DNA sequencing method that uses a simple biochemical reaction to encode the sequence of a DNA molecule into a highly measurable surrogate called an Xpandomer. This single molecule approach produces enough Xpandomer in a single drop reaction to sequence an entire human genome 1000X over. To achieve this, an Xpandomer replaces each DNA sequence with a sequence of large, high signal reporter molecules using the SBX molecular expansion technology. The DNA sequence is then read out as the Xpandomer reporters pass sequentially through a nanopore detector. SBX is a molecular engineering platform that benefits from core design principles that separate the multiple molecular functions. This systems approach enables efficient development and incorporation of improvements to SBX and is key to reconfiguring and optimizing Xpandomer measurement for different detection platforms.</p><p>http://www.stratosgenomics.com/stratos-genomics-technology</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/22995/bioinformatics-phd-postdoc-job-rejection</guid>
	<pubDate>Thu, 02 Jul 2015 08:52:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/22995/bioinformatics-phd-postdoc-job-rejection</link>
	<title><![CDATA[Bioinformatics PhD / PostDoc / Job Rejection]]></title>
	<description><![CDATA[<div><p>While your PhD or PostDoc application, it is more common that you got rejected by many professors. Don't disappoint reply it calmly.</p><p><img src="http://bioinformaticsonline.com/mod/photo/rejected1.png" alt="image" style="border: 0px; border: 0px;"></p><p>In grad school, I shared a house with three Bioinformatics PhD students. One, when he applied to a particular professor, received a letter that said, essentially, "If you are applying because you want to enrich yourself, great. If you are applying because you want a job, you should know that you won't get one." I am trying to tell you this is because if you, with a good background in Bioinformatics, are passing up opportunities, you must be a strong candidate in many areas. Enrich yourself.<br /><br /> So, my suggestion is take a deep breath, forgot about all. Don&rsquo;t take it personally. It's been usual processes while hunting for a good lab and professor. Take is positive, I am not sure why they reject, but don't worry perhaps the lab don't deserve you. Always remember there are billions of reasons not to hire someone for projects, especially in a research sector.<br /><br /> My suggestion, please do not whine about how you were a great research candidate for the post, and you just can't understand why they were so stupid as to have rejected you! This feeling will not win you any points in research, community. Especially, when in todays socially connected era everyone is linked. Remember, a nice E-mail saying, "I really wished to working with you on this project and I hope we cross paths again," is all you need to send to the professor. Send a thank you note to the professor. Thank them for the time they spend to judge you. In the future, If you and the professor (of your dream) are attending a bioinformatics conference, invite him/her to lunch (please remember to pay the bill). In today evolving scientific ere, always remember to build your solid network in order to get a job of interest. Join all possible networking sites like LinkedIn, ResearchGate, Acamedia, FB for the same reason. You as a researcher always build a bridge with student/researcher/colleague/professor who have the research potential to lead in research and hire you. Just because you didn't get this project, doesn't mean there isn't another that will open up in couple of month.<br /><br /> Mostly, jobs that are hard to get are hard to get. Only you can decide if the continued sacrifices are worth the expected payout. If it is, keep on plowing. Build relationships. Attend conferences.</p><p>Image ref @ JaSonYa</p></div>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/24264/cancer-research-database</guid>
	<pubDate>Tue, 01 Sep 2015 17:36:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/24264/cancer-research-database</link>
	<title><![CDATA[Cancer research database]]></title>
	<description><![CDATA[<p>Researchers in Andhra Pradesh have developed a database to identify genes that are common in tumours to provide their colleagues with easy access to insights into the genetic alterations in cancer.<br /> &nbsp;<br /> The database, hosted at the Sri Venkateswara University (SVU) in Tirupati, will integrate information on cancer genes and markers with experimental data.<br /> &nbsp;<br /> The <a href="http://cgmd.in/" target="_blank">Cancer Gene Markers Database</a> (CGMD) is meant to help scientists better understand tumour genes and markers at a molecular level by combining data with literature on treatment regimen and recent advances in cancer therapy.<br /> <br /> The database is free to access, and already includes 309 genes and 206 markers that correspond to 40 different human cancers. Accompanying literature comes from databases such as the United States&rsquo; <a href="http://www.ncbi.nlm.nih.gov/" target="_blank">National Center for Biotechnology Information</a> and the <a href="http://www.genome.jp/kegg/" target="_blank">Kyoto Encyclopedia of Genes and Genomes</a>. It also includes experimental data from <a href="http://www.ncbi.nlm.nih.gov/pubmed" target="_blank">PubMed</a>.<br /> <br /> In a paper <a href="http://dx.doi.org/10.1038/srep12035" target="_blank">published</a> last month in <em>Nature Scientific Reports</em>, the researchers from SVU&rsquo;s department of animal biotechnology, describes the need for a database for different genes and markers along with their molecular characteristics and pathway associations.</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26303/maker</guid>
	<pubDate>Sun, 07 Feb 2016 15:59:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26303/maker</link>
	<title><![CDATA[MAKER]]></title>
	<description><![CDATA[<p>MAKER is a portable and easily configurable genome annotation pipeline.Its purpose is to allow smaller eukaryotic and prokaryotic genome projects to independently annotate their genomes and to create genome databases. MAKER identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values.</p>
<p>More at http://www.yandell-lab.org/software/maker.html</p><p>Address of the bookmark: <a href="http://www.yandell-lab.org/software/maker.html" rel="nofollow">http://www.yandell-lab.org/software/maker.html</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26322/liftover</guid>
	<pubDate>Mon, 08 Feb 2016 15:45:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26322/liftover</link>
	<title><![CDATA[liftover]]></title>
	<description><![CDATA[<p><span>Convenient conversions between genome assemblie.&nbsp;The liftover package makes it easy to remap genomic coordinates to a different genome assembly. </span></p>
<p><span>More at https://github.com/aaronwolen/liftover<br></span></p>
<p><span>https://www.bioconductor.org/help/workflows/liftOver/</span></p><p>Address of the bookmark: <a href="https://github.com/aaronwolen/liftover" rel="nofollow">https://github.com/aaronwolen/liftover</a></p>]]></description>
	<dc:creator>Jitendra Narayan</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>
</item>

</channel>
</rss>