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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28787?offset=50</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/44650/manthey-research-group-%E2%80%93-evolutionary-genomics</guid>
  <pubDate>Thu, 22 Aug 2024 06:25:55 -0500</pubDate>
  <link></link>
  <title><![CDATA[Manthey Research Group – Evolutionary Genomics]]></title>
  <description><![CDATA[
<p>We focus on fundamental questions in genomics, ecology, and evolution. Our methods include fieldwork and labwork, but most of our time is spent analyzing genomics data using computational biology approaches.</p>

<p>Ant / bacteria co-evolution, landscape genomics, and population genomics<br />Vertebrate and/or invertebrate genome evolution</p>

<p>If you might be interested in joining our research group, send an email with your intent and why this group would potentially be a good fit for your future goals along with a CV / Resume to jdmanthey (at) gmail (dot) com</p>

<p>More at https://mantheylab.org/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/34912/list-of-cancer-genomics-research-web-resources</guid>
	<pubDate>Wed, 27 Dec 2017 20:33:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/34912/list-of-cancer-genomics-research-web-resources</link>
	<title><![CDATA[List of cancer genomics research web resources !]]></title>
	<description><![CDATA[<p>Major web resources for cancer genomics research</p><p>CGHub <br />https://cghub.ucsc.edu/ <br />Comprehensive data repository; huge data size</p><p>EGA <br />https://www.ebi.ac.uk/ega/ <br />Comprehensive data repository; huge data size</p><p>COSMIC <br />http://cancer.sanger.ac.uk <br />Largest somatic mutation database; genome sequencing paper curation</p><p>CPRG <br />http://www.broadinstitute.org/software/cprg <br />Interface for cancer program resources</p><p>GDAC <br />http://gdac.broadinstitute.org/ <br />Data analysis; automatic pipelines; user-friendly reports</p><p>SNP500Cancer <br />http://snp500cancer.nci.nih.gov <br />Sequence and genotype verification of SNPs</p><p>canEvolve <br />www.canevolve.org/ <br />Comprehensive analysis of tumor profile; Data from 90 studies involving more than 10,000 patients</p><p>MethyCancer <br />http://methycancer.psych.ac.cn <br />Relationship among DNA methylation, gene expression and cancer</p><p>SomamiR <br />http://compbio.uthsc.edu/SomamiR/ <br />Correlation between somatic mutation and microRNA; genome-wide displaying</p><p>cBioPortal <br />http://www.cbioportal.org/public-portal/ <br />Graphical summaries; gene alteration; processed data; visualization</p><p>UCSC Cancer Genomics Browser <br />https://genome-cancer.soe.ucsc.edu/ <br />Clinical information; gene expression; copy number variation; visualization</p><p>CGWB <br />https://cgwb.nci.nih.gov/ <br />Visualization; gene mutation and variation; automated analysis pipeline</p><p>GDSC <br />http://www.cancerrxgene.org <br />Drug sensitivity information; drug response information</p><p>canSAR <br />https://cansar.icr.ac.uk/ <br />Multidisciplinary information; drug discovery</p><p>NONCODE <br />http://www.noncode.org/ ncRNAs; <br />lncRNAs; up-to-date and comprehensive resource</p>]]></description>
	<dc:creator>biogeek</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/40882/troyanskaya-lab</guid>
  <pubDate>Tue, 04 Feb 2020 06:40:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[Troyanskaya Lab]]></title>
  <description><![CDATA[
<p>The goal of our research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods for systems-level pathway modeling through integrative analysis of genome-scale datasets. We apply these approaches in studying challenging biological problems, such as how pathways function in diverse cell types and how they change dynamically.</p>

<p>https://function.princeton.edu/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/43092/where-to-aproach-for-rd-funds-in-india</guid>
	<pubDate>Thu, 24 Jun 2021 01:04:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/43092/where-to-aproach-for-rd-funds-in-india</link>
	<title><![CDATA[Where to Aproach for R&amp;D Funds in India ?]]></title>
	<description><![CDATA[<p>Companies and governments do research and development (R&amp;D/ R'n'D/ R+D) to promote innovation in order to produce new goods or services and/or enhance existing product lines. R&amp;D covers all actions inside an organization aimed at boosting innovation, such as creating incubators, assisting innovators in scaling up their ideas, and cultivating an innovation culture.</p><p>Here are the list of all the research and development funding agencies in India.</p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/43092" length="73912" type="application/pdf" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/19921/which-of-the-followings-are-the-best-place-to-study-bioinformatics</guid>
	<pubDate>Sun, 28 Dec 2014 00:20:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/19921/which-of-the-followings-are-the-best-place-to-study-bioinformatics</link>
	<title><![CDATA[Which of the followings are the best place to study Bioinformatics ?]]></title>
	<description><![CDATA[<p>Bioinformatics is a major growth area and qualified Bioinformaticians are in high demand. An explosion in biological data has resulted from genome projects, next generation sequencing and other 'omics' techniques. Bioinformatics provides the tools to analyse and exploit such data sets.<br /><br />Can you please suggest me the best place to study bioinformatics ( Grad/PostGrad).</p>]]></description>
	<dc:creator>Reshma Khatun</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/20471/bioinformatics-scripts</guid>
	<pubDate>Thu, 22 Jan 2015 22:29:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/20471/bioinformatics-scripts</link>
	<title><![CDATA[Bioinformatics Scripts]]></title>
	<description><![CDATA[<p>Some of the useful bioinformatics scripts.</p>
<p>For example ... contig-stats.pl is a Perl script that will automatically describe features of a sequence assembly.</p>
<p>http://milkweedgenome.org/?q=scripts</p><p>Address of the bookmark: <a href="http://milkweedgenome.org/?q=scripts" rel="nofollow">http://milkweedgenome.org/?q=scripts</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/21443/a-guide-for-complete-r-beginners-getting-data-into-r</guid>
	<pubDate>Tue, 24 Feb 2015 20:15:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/21443/a-guide-for-complete-r-beginners-getting-data-into-r</link>
	<title><![CDATA[A guide for complete R beginners :- Getting data into R]]></title>
	<description><![CDATA[<p>For a beginner this can be is the hardest part, it is also the most important to get right.</p><p>It is possible to create a vector by typing data directly into R using the combine function &lsquo;c&rsquo;</p><blockquote><p><strong>x </strong></p></blockquote><p>same as</p><blockquote><p><strong>x </strong></p></blockquote><p>creates the vector x with the numbers between 1 and 5.</p><p>You can see what is in an object at any time by typing its name;</p><blockquote><p><strong>x</strong></p></blockquote><p>will produce the output<strong> &lsquo;[1] 1 2 3 4 5&prime;</strong></p><p>Note that names need to be quoted</p><blockquote><p><strong>daysofweek </strong><strong>&larr; c(&lsquo;Monday&rsquo;, &lsquo;Tuesday&rsquo;, &lsquo;Wednesday&rsquo;, &lsquo;Thursday&rsquo;, &lsquo;Friday&rsquo;);</strong></p></blockquote><p>Usually however you want to input from a file. We have touched on the &lsquo;read.table&rsquo; function already.</p><blockquote><p><strong>mydata </strong></p></blockquote><p>Now <strong>mydata</strong> is a data frame with multiple vectors</p><p>each vector can be identified by the default syntax</p><p>#if any of these are typed it will print to screen</p><blockquote><p><strong>mydata$V1 mydata$V2 mydata$V3 </strong></p></blockquote><p>By default the function assumes certain things from the file</p><ul>
<li>The file is a plain text file (there are function to read excel files: <em>not covered here</em>)</li>
<li>columns are separated by any number of tabs or spaces</li>
<li>there is the same number of data points in each column</li>
<li>there is no header row (labels for the columns)</li>
<li>there is no column with names for the rows** [I&rsquo;ll explain].</li>
</ul><p><span style="text-decoration: underline;">If any of these are false, we need to tell that to the function</span></p><p>If it has a header column</p><blockquote><p><strong>mydata <em>header=T also works</em></strong></p></blockquote><p>Note that there is a comma between different parts of the functions arguments</p><p>If there is one less column in the header row, then R assumes that the 1<sup>st</sup> column of data after the header are the row names</p><p>Now the vectors (columns) are identified by their name</p><p>#if any of these are typed it will print to screen</p><blockquote><p><strong>mydata$A mydata$B mydata$C </strong></p></blockquote><p># Summary about the whole data frame</p><blockquote><p><strong>summary(mydata)</strong></p></blockquote><p># Summary information of column A</p><blockquote><p><strong>summary(mydata$A) </strong></p></blockquote><p>We can shortcut having to type the data frame each time by attaching it</p><blockquote><p><strong>attach(mydata)</strong></p></blockquote><p># summary of column B as &lsquo;mydata&rsquo; is attached</p><blockquote><p><strong>summary(B)</strong></p></blockquote><p><span style="text-decoration: underline;">Two other important options for </span><em><span style="text-decoration: underline;">read.table</span></em></p><p>If is is separated only by tabs and has a header</p><blockquote><p><strong>mydata </strong></p></blockquote><p>Really useful if you have spaces in the contents of some columns, so R does not mess up reading the columns . However if the columns or of an uneven length it will tell you.</p><p>If you know that the file has uneven columns</p><blockquote><p><strong>mydata </strong></p></blockquote><p>This causes R to fill empty spaces in a columns with &lsquo;NA&rsquo; .</p><p>The last two examples will still work with our file and give the same result as with only headers=T</p><p><span style="text-decoration: underline;">Graphs</span></p><p>to get an idea of what R is capable of type</p><blockquote><p><strong>demo(graphics)</strong></p></blockquote><p>steps through the examples, and the code is printed to the screen</p><p>We will work with simpler examples that have immediate use to biologists.</p><p>Remember to get more information about the options to a function type &lsquo;?function&rsquo;</p><p><span style="text-decoration: underline;">Histogram of A</span><span style="text-decoration: underline;"></span></p><blockquote><p><strong>hist(mydata$A)</strong></p></blockquote><p>If there was more data we could increase the number of vertical columns with the option, breaks=50 (or another relevant number).</p><blockquote><p><strong>boxplot(mydata)</strong></p></blockquote><p>We can get rid of the need to type the data frame each time by using the <strong>attach</strong> function</p><p># if not already done so</p><blockquote><p><strong>attach(mydata) </strong></p><p><strong>boxplot(mydata$A, mydata$B, name=c(&ldquo;Value A&rdquo;, &ldquo;Value B&rdquo;) , ylab=&ldquo;Count of Something&rdquo;)</strong></p></blockquote><p>same as</p><blockquote><p><strong>boxplot(A, B, name=c(&ldquo;Value A&rdquo;, &ldquo;Value B&rdquo;) , ylab=&ldquo;Count of Something&rdquo;)</strong></p></blockquote><p><span style="text-decoration: underline;">Scatter plot</span></p><p># if not already done so</p><blockquote><p><strong>attach(mydata) </strong></p><p><strong>plot(A,B) # or plot(mydata$A, mydata$B)</strong></p></blockquote><p><strong><span style="text-decoration: underline;">SAVING an image</span></strong></p><p>Windows users (Rgui) RIGHT click on image and select which you want.</p><p><span style="text-decoration: underline;">These instructions work for everyone.</span></p><p>You need to create a new device of the type of file you need, then send the data to that device</p><p>to save as a png file (easy to load into the likes of powerpoint, also great for web applications.</p><blockquote><p><strong>png(&lsquo;filename&rsquo;) </strong></p><p><strong>boxplot(A, B, name=c(&ldquo;Value A&rdquo;, &ldquo;Value B&rdquo;) , ylab=&ldquo;Count of Something&rdquo;)</strong></p></blockquote><p>or to save as a pdf</p><blockquote><p><strong>pdf(&lsquo;filename&rsquo;) </strong></p><p><strong>boxplot(A, B, name=c(&ldquo;Value A&rdquo;, &ldquo;Value B&rdquo;) , ylab=&ldquo;Count of Something&rdquo;)</strong></p></blockquote><p><span style="text-decoration: underline;">Note</span></p><ul>
<li>Nothing will appear on screen, the output is going to the file</li>
<li>Also it may not be saved immediately but will once the device (or R) is turned quit.</li>
</ul><p>To quit R type</p><p><strong>q() # </strong>If you save your session, next time you start R, you will have your data preloaded.</p><p>Or if you want to remain in R</p><blockquote><pre><strong>dev.off() #</strong>turns of the png (or pdf etc) device, thus forces the data to save</pre></blockquote>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/22017/binc-2015</guid>
	<pubDate>Sat, 11 Apr 2015 20:35:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/22017/binc-2015</link>
	<title><![CDATA[BINC 2015 !!!]]></title>
	<description><![CDATA[<p>Pondicherry University,Puducherry,on behalf of Department of Biotechnology, Government of India, will conduct the BINC examination in2015. The objective of this examination is to certify bioinformatics professionals, trained formally as well as self-trained.Registration will open from March 9,2015 to April 30,2015. Pondicherry University, Puducherry has been identified as a nodal agency by the Department of Biotechnology, Govt. of India to coordinate this examination along with nine centres namely, Pune University, Pune; Anna University, Chennai; Calcutta University, Kolkata; Institute of Bioinformatics &amp; Applied Biotechnology, Bangalore; North-Eastern Hill University, Shillong, University of Hyderabad, Hyderabad; University of Kerala, Thiruvananthapuram; Jawaharlal Nehru University, New Delhi and Assam Agricultural University, Guwahati. In the BINC 2013 examination,17 candidates were certified. DBT has agreed to fund Research fellowships for all the BINC qualified Indian nationals to pursue Ph.D. in Indian Institutes/Universities. Note that the candidate must possess a postgraduate degree(or equivalent) &amp; meet the criteria of the institutes/universities in order to avail research fellowship. In addition, cash prize of Rs. 10,000/- will be awarded to the top 10 BINC qualifiers.</p><p>More at http://www.binc.co.in/College/Index_New.aspx</p><p>BINC notification http://www.binc.co.in/PdfDocuments/Notification.pdf</p><p>Few dates to remember:</p><p>Starting of online submission of application: March 9, 2015<br />Last date for submission of application: April 30,2015<br />Examination consists of two parts:<br />Part I (Paper I) : June 7, 2015 (10 AM-12 PM)<br />Part II ( Paper II &amp; III) :June 28, 2015 (9 AM-12 PM &amp; 2 PM-4 PM)</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/22053/binc-sample-question-paper</guid>
	<pubDate>Thu, 16 Apr 2015 09:16:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/22053/binc-sample-question-paper</link>
	<title><![CDATA[BINC Sample Question Paper !!!]]></title>
	<description><![CDATA[<p>BINC sample question paper. Wish you all the best for BINC examination.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/22053" length="4041" type="text/plain" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22388/perl-one-liner-basics</guid>
	<pubDate>Sun, 24 May 2015 09:28:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22388/perl-one-liner-basics</link>
	<title><![CDATA[Perl One liner basics !!]]></title>
	<description><![CDATA[<p>Perl has a ton of command line switches (see perldoc perlrun), but I'm just going to cover the ones you'll commonly need to debug code. The most important switch is -e, for execute (or maybe "engage" :) ). The -e switch takes a quoted string of Perl code and executes it. For example:<br /><br />$ perl -e 'print "Hello, World!\n"'<br />Hello, World!<br /><br />It's important that you use single-quotes to quote the code for -e. This usually means you can't use single-quotes within the one liner code. If you're using Windows cmd.exe or PowerShell, you must use double-quotes instead.<br /><br />I'm always forgetting what Perl's predefined special variables do, and often test them at the command line with a one liner to see what they contain. For instance do you remember what $^O is?<br /><br />$ perl -e 'print "$^O\n"'<br />linux<br /><br />It's the operating system name. With that cleared up, let's see what else we can do. If you're using a relatively new Perl (5.10.0 or higher) you can use the -E switch instead of -e. This turns on some of Perl's newer features, like say, which prints a string and appends a newline to it. This saves typing and makes the code cleaner:<br /><br />$ perl -E 'say "$^O"'<br />linux<br /><br />Pretty handy! say is a nifty feature that you'll use again and again.</p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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