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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28997?offset=1260</link>
	<atom:link href="https://bioinformaticsonline.com/related/28997?offset=1260" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/23121/senior-sas-programmer-urgent-role-permanant-welwyn-garden-city-uk</guid>
  <pubDate>Fri, 03 Jul 2015 08:14:23 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior SAS Programmer - URGENT ROLE - Permanant - Welwyn Garden City - UK]]></title>
  <description><![CDATA[
<p>SAS Programmer URGENTLY required !! My client is looking for an experienced Senior SAS Programmer, to join their bubbly dynamic team in Welwyn Garden City. You must have experience within SAS and/or R programming language. I am looking for someone with a background within either Life Sciences, Statistics, Computer Science, Bioinformatics etc. I am looking for someone with leadership qualities, you must have excellent analyst skills. Please call Dareen Evans on 01772 278050 or email your cv to dareen.evans@itworkshealth.co.uk</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2349/bioinformatics-understanding-of-living-systems-through-information-science</guid>
	<pubDate>Wed, 14 Aug 2013 11:50:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2349/bioinformatics-understanding-of-living-systems-through-information-science</link>
	<title><![CDATA[Bioinformatics -- Understanding of living systems through  information science]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/6Ovd_GOM9-g" frameborder="0" allowfullscreen></iframe>Recently, the progress of the Human Genome Project, aiming to decode all human DNA sequences, has highlighted a research field called bioinformatics. In this new field, computers and techniques from information science are not just used as tools to advance life science research; they're expected to have a major impact on how we think about the life sciences.

Q. The main feature of bioinformatics is, it utilizes computers to analyze life. One is example is the genome. In all organisms, DNA contains genetic information, and this is called the genome. But the amount of information involved is huge, so recently, it's been read using next-generation sequencers, and analyzed by computers. In bioinformatics research, what we do is utilize those genome information to investigate the principles of life.

As an organism evolves, its genome sequence changes through sudden mutations. Additionally, at the genome level, mutations called rearrangements, such as inversions, transpositions, and duplications, occur. 

The genome comparison system developed by the Sakakibara Lab calculates homologous sequences called anchors, which are conserved between species. If the genome is considered as a long text, then anchors can be thought of as words.

Q. We're coming to understand the genomes of various organisms - not just humans, but monkeys, chimpanzees, bacteria, and so on. The first method used to analyze a genome is comparing it with the genomes of other organisms, to see where it's the same and where it's different. In that way, the content of the genome is decoded bit by bit, using computers. By contrast, in our method, we've developed software called Murasaki, which we also use to analyze large genomes, by comparing them with those of other organisms.

The Sakakibara Lab uses a next-generation sequencer at Keio University, along with a cluster machine with hundreds of CPUs. In this way, the Lab is analyzing genome mutations that cause cancer, and the genome of the natto production strain Bacillus subtilis.

Until now, genome analysis could only be done in national-scale projects. But now, next-generation sequencer development has made genome analysis possible in an ordinary lab. In a world-first achievement, the Sakakibara Lab has decoded the natto bacillus genome, through analysis using Keio's next-generation sequencer.

Q. In the future, biology and the life sciences may become almost entirely information science and computer science. And in healthcare, that may enable us, for example, to predict whether individuals are susceptible to cancer, or to certain lifestyle-related diseases, by understanding their personal genome data. So, I think it's amply possible that we can make use of such information effectively, to help people live longer and be free from disease, by thinking about their lifestyle habits.
 
Bioinformatics is only two decades old. In this field, many areas are still unknown. Professor Sakakibara, having been involved since the beginning, will continue tackling new, challenging research projects.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34552/edit-distance-application-in-bioinformatics</guid>
	<pubDate>Thu, 07 Dec 2017 08:46:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34552/edit-distance-application-in-bioinformatics</link>
	<title><![CDATA[Edit distance application in bioinformatics !]]></title>
	<description><![CDATA[<p>There are other popular measures of&nbsp;<a href="https://en.wikipedia.org/wiki/Edit_distance" title="Edit distance">edit distance</a>, which are calculated using a different set of allowable edit operations. For instance,</p><ul>
<li>the&nbsp;<a href="https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance" title="Damerau&ndash;Levenshtein distance">Damerau&ndash;Levenshtein distance</a>&nbsp;allows insertion, deletion, substitution, and the&nbsp;<a href="https://en.wikipedia.org/wiki/Transposition_(mathematics)" title="Transposition (mathematics)">transposition</a>&nbsp;of two adjacent characters;</li>
<li>the&nbsp;<a href="https://en.wikipedia.org/wiki/Longest_common_subsequence_problem" title="Longest common subsequence problem">longest common subsequence</a>&nbsp;(LCS) distance allows only insertion and deletion, not substitution;</li>
<li>the&nbsp;<a href="https://en.wikipedia.org/wiki/Hamming_distance" title="Hamming distance">Hamming distance</a>&nbsp;allows only substitution, hence, it only applies to strings of the same length.</li>
<li>the&nbsp;<a href="https://en.wikipedia.org/wiki/Jaro_distance" title="Jaro distance">Jaro distance</a>&nbsp;allows only&nbsp;<a href="https://en.wikipedia.org/wiki/Transposition_(mathematics)" title="Transposition (mathematics)">transposition</a>.</li>
</ul><p>&nbsp;</p><pre><span>use</span> Text<span>::</span>Levenshtein <span>qw</span><span>(</span>distance<span>);</span>

 <span>print</span> <span>distance</span><span>(</span><span>"foo"</span><span>,</span><span>"four"</span><span>);</span>
 <span># prints "2"</span>

 <span>my</span> <span>@words</span>     <span>=</span> <span>qw</span><span>/ four foo bar /</span><span>;</span>
 <span>my</span> <span>@distances</span> <span>=</span> <span>distance</span><span>(</span><span>"foo"</span><span>,</span><span>@words</span><span>);</span>

 <span>print</span> <span>"@distances"</span><span>;</span>
 <span># prints "2 0 3"</span><br /><br /><br /></pre><pre><span>use</span> Algorithm<span>::</span>LCSS <span>qw</span><span>(</span> LCSS CSS CSS_Sorted <span>);</span>
    <span>my</span> <span>$lcss_ary_ref</span> <span>=</span> <span>LCSS</span><span>(</span> <span>\</span><span>@SEQ1</span><span>,</span> <span>\</span><span>@SEQ2</span> <span>);</span>  <span># ref to array</span>
    <span>my</span> <span>$lcss_string</span>  <span>=</span> <span>LCSS</span><span>(</span> <span>$STR1</span><span>,</span> <span>$STR2</span> <span>);</span>    <span># string</span>
    <span>my</span> <span>$css_ary_ref</span> <span>=</span> <span>CSS</span><span>(</span> <span>\</span><span>@SEQ1</span><span>,</span> <span>\</span><span>@SEQ2</span> <span>);</span>    <span># ref to array of arrays</span>
    <span>my</span> <span>$css_str_ref</span> <span>=</span> <span>CSS</span><span>(</span> <span>$STR1</span><span>,</span> <span>$STR2</span> <span>);</span>      <span># ref to array of strings</span>
    <span>my</span> <span>$css_ary_ref</span> <span>=</span> <span>CSS_Sorted</span><span>(</span> <span>\</span><span>@SEQ1</span><span>,</span> <span>\</span><span>@SEQ2</span> <span>);</span>  <span># ref to array of arrays</span>
    <span>my</span> <span>$css_str_ref</span> <span>=</span> <span>CSS_Sorted</span><span>(</span> <span>$STR1</span><span>,</span> <span>$STR2</span> <span>);</span>    <span># ref to array of strings<br /><br /><br /><br /></span></pre><p>There are many different modules on CPAN for calculating the edit distance between two strings. Here's just a selection.</p><p><a href="http://search.cpan.org/perldoc?Text%3A%3ALevenshteinXS">Text::LevenshteinXS</a>&nbsp;and&nbsp;<a href="http://search.cpan.org/perldoc?Text%3A%3ALevenshtein%3A%3AXS">Text::Levenshtein::XS</a>&nbsp;are both versions of the Levenshtein algorithm that require a C compiler, but will be a lot faster than this module.</p><p>The Damerau-Levenshtein edit distance is like the Levenshtein distance, but in addition to insertion, deletion and substitution, it also considers the transposition of two adjacent characters to be a single edit. The module&nbsp;<a href="http://search.cpan.org/perldoc?Text%3A%3ALevenshtein%3A%3ADamerau">Text::Levenshtein::Damerau</a>&nbsp;defaults to using a pure perl implementation, but if you've installed&nbsp;<a href="http://search.cpan.org/perldoc?Text%3A%3ALevenshtein%3A%3ADamerau%3A%3AXS">Text::Levenshtein::Damerau::XS</a>&nbsp;then it will be a lot quicker.</p><p><a href="http://search.cpan.org/perldoc?Text%3A%3AWagnerFischer">Text::WagnerFischer</a>&nbsp;is an implementation of the Wagner-Fischer edit distance, which is similar to the Levenshtein, but applies different weights to each edit type.</p><p><a href="http://search.cpan.org/perldoc?Text%3A%3ABrew">Text::Brew</a>&nbsp;is an implementation of the Brew edit distance, which is another algorithm based on edit weights.</p><p><a href="http://search.cpan.org/perldoc?Text%3A%3AFuzzy">Text::Fuzzy</a>&nbsp;provides a number of operations for partial or fuzzy matching of text based on edit distance.&nbsp;<a href="http://search.cpan.org/perldoc?Text%3A%3AFuzzy%3A%3APP">Text::Fuzzy::PP</a>&nbsp;is a pure perl implementation of the same interface.</p><p><a href="http://search.cpan.org/perldoc?String%3A%3ASimilarity">String::Similarity</a>&nbsp;takes two strings and returns a value between 0 (meaning entirely different) and 1 (meaning identical). Apparently based on edit distance.</p><p><a href="http://search.cpan.org/perldoc?Text%3A%3ADice">Text::Dice</a>&nbsp;calculates&nbsp;<a href="https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient">Dice's coefficient</a>&nbsp;for two strings. This formula was originally developed to measure the similarity of two different populations in ecological research.</p><pre><span>&nbsp;</span></pre>]]></description>
	<dc:creator>Neel</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4547/bioinformatics-infrastructure-facility</guid>
  <pubDate>Sun, 15 Sep 2013 09:22:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Infrastructure Facility]]></title>
  <description><![CDATA[
<p>The Bioinformatics Infrastructure Facility has started working in the year 2007 at Presidency College, Kolkata. It is one of the premier institutes of India and boasts of a rich heritage and great alumni. The Infrastructure Facility has a dedicated team headed by Sayak Ganguli and ably supported by Priayanka Dhar. The coordinator of the facility is Abhijit Datta of the Post Graduate Department of Botany. The lab mainly focusses on the analysis of the RNA Induced Silencing Complex. Recent highlights include the presentation of a paper at the RNAi World Congress.</p>

<p>More @ http://bioinfo-presiuniv.edu.in/index.php</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35534/awk-for-bioinformatician-and-computational-biologist</guid>
	<pubDate>Tue, 06 Feb 2018 14:54:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35534/awk-for-bioinformatician-and-computational-biologist</link>
	<title><![CDATA[Awk for Bioinformatician and computational biologist]]></title>
	<description><![CDATA[<p>Awk is a programming language which allows easy manipulation of structured data and is mostly used for pattern scanning and processing. It searches one or more files to see if they contain lines that match with the specified patterns and then perform associated actions. The basic syntax is:</p><blockquote><p><br />awk '/pattern1/ {Actions}<br /> /pattern2/ {Actions}' file</p></blockquote><p><br />The working of Awk is as follows<br />Awk reads the input files one line at a time.<br />For each line, it matches with given pattern in the given order, if matches performs the corresponding action.<br />If no pattern matches, no action will be performed.<br />In the above syntax, either search pattern or action are optional, But not both.<br />If the search pattern is not given, then Awk performs the given actions for each line of the input.<br />If the action is not given, print all that lines that matches with the given patterns which is the default action.<br />Empty braces with out any action does nothing. It wont perform default printing operation.<br />Each statement in Actions should be delimited by semicolon.<br />Say you have data.tsv with the following contents:</p><p><br />$ cat data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />By default Awk prints every line from the file.</p><p><br />$ awk '{print;}' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />We print the line which matches the pattern contig3</p><p><br />$ awk '/contig3/' data/test.tsv<br />contig3 ACTTATATATATATA<br />Awk has number of builtin variables. For each record i.e line, it splits the record delimited by whitespace character by default and stores it in the $n variables. If the line has 5 words, it will be stored in $1, $2, $3, $4 and $5. $0 represents the whole line. NF is a builtin variable which represents the total number of fields in a record.</p><p><br />$ awk '{print $1","$2;}' data/test.tsv<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT</p><p>$ awk '{print $1","$NF;}' data/test.tsv<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT</p><p><br />Awk has two important patterns which are specified by the keyword called BEGIN and END. The syntax is as follows:</p><blockquote><p>BEGIN { Actions before reading the file}<br />{Actions for everyline in the file} <br />END { Actions after reading the file }</p></blockquote><p><br />For example,<br />$ awk 'BEGIN{print "Header,Sequence"}{print $1","$2;}END{print "-------"}' data/test.tsv<br />Header,Sequence<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT<br />------- <br />We can also use the concept of a conditional operator in print statement of the form print CONDITION ? PRINT_IF_TRUE_TEXT : PRINT_IF_FALSE_TEXT. For example, in the code below, we identify sequences with lengths &gt; 14:</p><p>$ awk '{print (length($2)&gt;14) ? $0"&gt;14" : $0"&lt;=14";}' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG&gt;14<br />contig2 ACTTTATATATT&lt;=14<br />contig3 ACTTATATATATATA&gt;14<br />contig4 ACTTATATATATATA&gt;14<br />contig5 ACTTTATATATT&lt;=14<br />We can also use 1 after the last block {} to print everything (1 is a shorthand notation for {print $0} which becomes {print} as without any argument print will print $0 by default), and within this block, we can change $0, for example to assign the first field to $0 for third line (NR==3), we can use:</p><p>$ awk 'NR==3{$0=$1}1' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT<br />You can have as many blocks as you want and they will be executed on each line in the order they appear, for example, if we want to print $1 three times (here we are using printf instead of print as the former doesn't put end-of-line character),</p><p>$ awk '{printf $1"\t"}{printf $1"\t"}{print $1}' data/test.tsv<br />contig1 contig1 contig1<br />contig2 contig2 contig2<br />contig3 contig3 contig3<br />contig4 contig4 contig4<br />contig5 contig5 contig5 <br />Although, we can also skip executing later blocks for a given line by using next keyword:</p><p>$ awk '{printf $1"\t"}NR==3{print "";next}{print $1}' data/test.tsv<br />contig1 contig1<br />contig2 contig2<br />contig3 <br />contig4 contig4<br />contig5 contig5</p><p>$ awk 'NR==3{print "";next}{printf $1"\t"}{print $1}' data/test.tsv<br />contig1 contig1<br />contig2 contig2</p><p>contig4 contig4<br />contig5 contig5<br />You can also use getline to load the contents of another file in addition to the one you are reading, for example, in the statement given below, the while loop will load each line from test.tsv into k until no more lines are to be read:</p><p>$ awk 'BEGIN{while((getline k &lt;"data/test.tsv")&gt;0) print "BEGIN:"k}{print}' data/test.tsv<br />BEGIN:contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />BEGIN:contig2 ACTTTATATATT<br />BEGIN:contig3 ACTTATATATATATA<br />BEGIN:contig4 ACTTATATATATATA<br />BEGIN:contig5 ACTTTATATATT<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />You can also store data in the memory with the syntax VARIABLE_NAME[KEY]=VALUE which you can later use through for (INDEX in VARIABLE_NAME) command:</p><p>$ awk '{i[$1]=1}END{for (j in i) print j"&lt;="i[j]}' data/test.tsv<br />contig1&lt;=1<br />contig2&lt;=1<br />contig3&lt;=1<br />contig4&lt;=1<br />contig5&lt;=1</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2492/plos-computational-biology-translational-bioinformatics-educational-resources</guid>
	<pubDate>Fri, 16 Aug 2013 12:24:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2492/plos-computational-biology-translational-bioinformatics-educational-resources</link>
	<title><![CDATA[PLOS Computational Biology: Translational Bioinformatics educational resources]]></title>
	<description><![CDATA[<p>PLOS present collection of Education articles:&nbsp; &ldquo;Translational Bioinformatics&rdquo;. This collection is presented as an online &ldquo;book&rdquo; which could serve as a reference tool for a graduate level introductory course, marking a step in an exciting new direction for the Education section of the journal.</p>
<p>Blog : http://blogs.plos.org/biologue/2012/12/28/translational-bioinformatics-plos-computational-biology-presents-an-educational-resource-for-an-emerging-field/</p>
<p>Educational Material : http://www.ploscollections.org/article/browseIssue.action?issue=info:doi/10.1371/issue.pcol.v03.i11</p><p>Address of the bookmark: <a href="http://www.ploscollections.org/article/browseIssue.action?issue=info:doi/10.1371/issue.pcol.v03.i11" rel="nofollow">http://www.ploscollections.org/article/browseIssue.action?issue=info:doi/10.1371/issue.pcol.v03.i11</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/36211/project-based-approach-to-improve-bioinformatics-education-with-skilled-and-meaningful-access-to-omics-data</guid>
	<pubDate>Wed, 11 Apr 2018 13:31:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/36211/project-based-approach-to-improve-bioinformatics-education-with-skilled-and-meaningful-access-to-omics-data</link>
	<title><![CDATA[Project-based approach to improve bioinformatics education with skilled and meaningful access to omics data]]></title>
	<description><![CDATA[<p>Pine Biotech has been collaborating with Loyola University of New Orleans on piloting a new approach to bioinformatics education using the intuitive and logic-drive bioinformatics platform T-BioInfo.</p><p>https://edu.t-bio.info/collaborative-model-bioinformatics-education-combining-biologically-inspired-bioinformatics-project-based-learning/</p>]]></description>
	<dc:creator>eliabrodsky</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2699/translational-bioinformatics-transforming-300-billion-points-of-data</guid>
	<pubDate>Tue, 20 Aug 2013 19:03:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2699/translational-bioinformatics-transforming-300-billion-points-of-data</link>
	<title><![CDATA[Translational Bioinformatics: Transforming 300 Billion Points of Data]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/o4KNG7nd938" frameborder="0" allowfullscreen></iframe>Translational Bioinformatics: Transforming 300 Billion Points of Data into Diagnostics, Therapeutics, and New Insights into Disease      
      
Air date:  Wednesday, June 20, 2012, 3:00:00 PM
Time displayed is Eastern Time, Washington DC Local  
 
Description:  There is an urgent need to translate genome-era discoveries into clinical utility, but the difficulties in making bench-to-bedside translations haven't been well described. The nascent field of translational bioinformatics may help. Dr. Butte's lab at Stanford University builds and applies tools that convert more than 300 billion points of molecular, clinical, and epidemiological data (measured by researchers and clinicians over the past decade) into diagnostics, therapeutics, and new insights into disease. Dr. Butte, a bioinformatician and pediatric endocrinologist, will highlight his lab's work on using publicly available molecular measurements to find new uses for drugs, discovering new treatable mechanisms of disease in type 2 diabetes, and evaluating patients presenting with whole genomes sequenced. 

The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. 

For more information, visit: 
The NIH Director's Wednesday Afternoon Lecture Series  
Author:  Atul Butte, M.D., Ph.D., Stanford University  
Runtime:  01:07:42  
Permanent link:  http://videocast.nih.gov/launch.asp?17321]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/38029/biologist-versus-computational-biologist</guid>
	<pubDate>Mon, 29 Oct 2018 04:23:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/38029/biologist-versus-computational-biologist</link>
	<title><![CDATA[Biologist versus computational biologist !]]></title>
	<description><![CDATA[<p>This is how it work :)</p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/38029" length="69305" type="image/png" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/2741/bioinformatician-dreams</guid>
	<pubDate>Wed, 21 Aug 2013 10:50:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/2741/bioinformatician-dreams</link>
	<title><![CDATA[Bioinformatician Dreams]]></title>
	<description><![CDATA[<p>Bioinformatician life is interconnected, they always dream for a powerful server, little more space on server as they are generating lots of data per run, dream to publish results in good impact journals, meetings reminders :) and research analysis off course!!!&nbsp;</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/2741" length="557537" type="image/png" />
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