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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26303?offset=170</link>
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	<item>
	<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>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22403/ryan-e-mills-lab</guid>
  <pubDate>Tue, 26 May 2015 09:29:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Ryan E. Mills Lab]]></title>
  <description><![CDATA[
<p>Our research group is primarily focused on the analysis of whole genome sequence data to identify genetic variation (primarily structural variation) and examine their potential functional impact in disease phenotypes. We are particularly interested in analyzing complex regions of the genome that are not easily resolved through modern sequencing approaches and which may exhibit interesting mechanistic origins.</p>

<p>We are also interested in the large-scale integration of genomic, expression, methylation and proteomic data sets, as well as the application of whole genome sequence analysis in clinical diagnostics. </p>

<p>More at http://millslab.ccmb.med.umich.edu/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22570/frequent-words-problem-solution-by-perl</guid>
	<pubDate>Tue, 09 Jun 2015 23:38:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22570/frequent-words-problem-solution-by-perl</link>
	<title><![CDATA[Frequent words problem solution by Perl]]></title>
	<description><![CDATA[<div><p>Solved with perl <a href="http://rosalind.info/problems/1a/">http://rosalind.info/problems/1a/</a></p><p>#Find the most frequent k-mers in a string.<br />#Given: A DNA string Text and an integer k.<br />#Return: All most frequent k-mers in Text (in any order).<br /><br />use strict;<br />use warnings;<br /><br />my $string="ACGTTGCATGTCGCATGATGCATGAGAGCT";<br />my $kmer=4; <br />my %myHash;<br />my $max=0;<br /><br />for (my $aa=0; $aa&lt;=(length($string)-4); $aa++) {<br />&nbsp;&nbsp; &nbsp;my $myStr=substr&nbsp; $string, $aa,$kmer;<br />&nbsp;&nbsp; &nbsp;#print "$myStr\n";<br />&nbsp;&nbsp; &nbsp;my $km=kmerMatch ($string, $myStr, $kmer);<br />&nbsp;&nbsp; &nbsp;if ($km &gt; $max) { $max = $km;}<br />&nbsp;&nbsp; &nbsp;#print "$km\t$myStr\n";<br />&nbsp;&nbsp; &nbsp;$myHash{$myStr}=$km;<br />&nbsp;&nbsp; &nbsp;<br />}<br /><br />#Print all key which have matching values<br />foreach my $name (keys %myHash){<br />&nbsp;&nbsp;&nbsp; print "$name " if $myHash{$name} == $max;<br />}<br /><br />sub kmerMatch { #Check the exact matching kmers with sliding window<br />my ($string, $myStr, $kmer)=@_;<br />my $count=0;<br />for (my $aa=0; $aa&lt;=(length($string)-4); $aa++) {<br />&nbsp;&nbsp; &nbsp;my $myWin=substr&nbsp; $string, $aa,$kmer;<br />&nbsp;&nbsp; &nbsp;if ($myWin eq $myStr) {<br />&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;#print "$myWin eq $myStr\n";<br />&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;$count++;<br />&nbsp;&nbsp; &nbsp;}<br />}<br />return $count;<br />}</p></div>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22572/clump-finding-problem-solved-with-perl</guid>
	<pubDate>Wed, 10 Jun 2015 00:17:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22572/clump-finding-problem-solved-with-perl</link>
	<title><![CDATA[Clump Finding Problem Solved with Perl]]></title>
	<description><![CDATA[<p>The question at http://rosalind.info/problems/1d/</p><p>Script are moved to&nbsp;http://bioinformaticsonline.com/snippets/view/34633/clump-finding-problem-solved-with-perl</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/22906/at-what-age-did-you-gain-passion-in-bioinformatics</guid>
	<pubDate>Tue, 23 Jun 2015 10:39:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/22906/at-what-age-did-you-gain-passion-in-bioinformatics</link>
	<title><![CDATA[At what age did you gain passion in Bioinformatics?]]></title>
	<description><![CDATA[<p>Most of the bioinformatician were biologist ( yeah ... not all ;), and at later stage they gain a passion in Bioinformatics and learn it. When did you get inclined towards computational analysis of biological data?</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/23149/raphael-lab</guid>
  <pubDate>Sat, 04 Jul 2015 19:05:29 -0500</pubDate>
  <link></link>
  <title><![CDATA[Raphael Lab]]></title>
  <description><![CDATA[
<p>Raphael Lab research is focused on Bioinformatics and Computational Biology.</p>

<p>Current research interests include next-generation DNA sequencing, structural variation, genome rearrangements in cancer and evolution, and network analysis of somatic mutations in cancer. Earlier research included topics in comparative genomics, multiple sequence alignment, and motif finding.</p>

<p>More athttp://compbio.cs.brown.edu/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/23633/biorg</guid>
  <pubDate>Tue, 04 Aug 2015 20:52:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[BioRG]]></title>
  <description><![CDATA[
<p>This research group works on problems from the fields of Bioinformatics, Biotechnology, Data Mining, and Information Retrieval. The group's research projects includes Comparative Genomics of Bacterial genomes, Metagenomics, Genomic databases, Pattern Discovery in sequences and structures, micro-array data analysis, prediction of regulatory elements, primer design, probe design, phylogenetic analysis, medical image processing, image analysis, data integration, data mining, information retrieval, knowledge discovery in electronic medical records, and more. </p>

<p>More at http://biorg.cis.fiu.edu/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23892/bioinformatics-made-easy-search-bioinformatics-tools-and-run-genomic-analysis-in-the-cloud</guid>
	<pubDate>Thu, 20 Aug 2015 02:21:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23892/bioinformatics-made-easy-search-bioinformatics-tools-and-run-genomic-analysis-in-the-cloud</link>
	<title><![CDATA[Bioinformatics Made Easy Search: Bioinformatics tools and run genomic analysis in the cloud]]></title>
	<description><![CDATA[<p>InsideDNA makes hundreds of bioinformatics tools immediately available to run via an easy-to-use web interface and allows an accurate search across all functions, tools and pipelines.</p>
<p>With InsideDNA, you can upload and store your own genomic/genetic datasets in a limitless cloud space, and instantly analyze it with a powerful compute instance, without any tool installation or set up hassle.</p>
<p>More at https://insidedna.me/</p><p>Address of the bookmark: <a href="https://insidedna.me/" rel="nofollow">https://insidedna.me/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25284/rajiv-gandhi-centre-for-biotechnology-rgcb-invites-applications-for-the-following-three-faculty-scientist</guid>
  <pubDate>Tue, 24 Nov 2015 22:13:16 -0600</pubDate>
  <link></link>
  <title><![CDATA[Rajiv Gandhi Centre for Biotechnology (RGCB) invites applications for the following three faculty scientist]]></title>
  <description><![CDATA[
<p>Scientist Positions<br />Advt. No.RGCB Advt./SCI 2015/1<br /> <br />November 11, 2015</p>

<p>Rajiv Gandhi Centre for Biotechnology (RGCB) invites applications for the following three faculty scientist positions:</p>

<p>Scientist E-II or F in Bioinformatics &amp; Computational Biology</p>

<p>SCIENTIST E-II OR F IN COMPUTATIONAL BIOLOGY &amp; BIOINFORMATICS</p>

<p>Highly motivated and innovative individual who will pursue basic research, solve biological problems with emphasis on computational and quantitative experimental methods and build active bridges to translational research. The scientist will also provide computational biology support to ongoing research programs in disease biology, provide assistance to analyze complex data sets generated by RGCB scientists and collaborators inclusive of including high dimensional “omics” data and next generation sequencing data, such as whole genome, exome, RNA-seq and ChIP-seq as well as provide leadership for high quality training for junior scientists and regular teaching programs of the institute. Areas of research of interest to RGCB include but are not limited to computational, systems, or quantitative biology with applications to cell biology, developmental biology, metabolism, genomics, proteomics, biophysics, biological information systems, network pharmacology, drug design and cancer research. The scientist’s responsibilities include efforts for the integration of DNA variant annotation with statistical genetic analysis methods including linkage, imputation and association methods, adopting novel and innovative methodologies to analyze, integrate and interpret high dimensional data sets, provision of annotation to robust genetics and genomics findings using several data sources and methods, data management of exploratory clinical and R&amp;D studies in partnership with other lines of genetic data generated from internal and external studies, delivery and documentation of genomic information to support genetic studies, ensuring high-quality genetic and genomic data is incorporated into exploratory- clinical research programs, developing tools that make maximum use of multiple data sources to support annotation of DNA variation and contributes to systems biology initiatives within RGCB </p>

<p>More at http://rgcb.res.in/scientist-positions/</p>

<p>Application Form http://rgcb.res.in/wp-content/uploads/2015/11/APPLICATION-FORMAT-FOR-SCIENTISTS.docx</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26827/kamaleshwar-singh-lab</guid>
  <pubDate>Fri, 25 Mar 2016 10:46:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[Kamaleshwar Singh Lab]]></title>
  <description><![CDATA[
<p>The focus of Dr. Singh’s research and teaching is on the molecular mechanistic basis for environmental carcinogen-induced genetic (DNA damage) and epigenetic changes, and susceptibility to human cancer development</p>

<p>More at http://www.tiehh.ttu.edu/dr.-kamaleshwar-singh.html</p>
]]></description>
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