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	<title>Comments on: Keep focused, keep an up to date list of ten specific questions</title>
	<atom:link href="http://www.bioinformaticszen.com/2007/05/ten-specific-questions/feed/" rel="self" type="application/rss+xml" />
	<link>http://www.bioinformaticszen.com/2007/05/ten-specific-questions/</link>
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	<pubDate>Sun, 07 Sep 2008 03:10:57 +0000</pubDate>
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		<title>By: Giovanni</title>
		<link>http://www.bioinformaticszen.com/2007/05/ten-specific-questions/#comment-785</link>
		<dc:creator>Giovanni</dc:creator>
		<pubDate>Sun, 27 May 2007 18:21:03 +0000</pubDate>
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		<description>Your video are very cool! :)</description>
		<content:encoded><![CDATA[<p>Your video are very cool! <img src='http://www.bioinformaticszen.com/wp-includes/images/smilies/icon_smile.gif' alt=':)' class='wp-smiley' /></p>
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		<title>By: Neil</title>
		<link>http://www.bioinformaticszen.com/2007/05/ten-specific-questions/#comment-631</link>
		<dc:creator>Neil</dc:creator>
		<pubDate>Mon, 21 May 2007 04:47:14 +0000</pubDate>
		<guid isPermaLink="false">http://www.bioinformaticszen.com/2007/05/ten-specific-questions/#comment-631</guid>
		<description>I think this post identifies a key problem of being "the computer guy" in a biological department.  It's easy to fall into a kind of IT support role.  You keep the servers running, install software for people, write little scripts to analyse data for colleagues.  It's hard to interact with your peers, most of whom are wrapped up in the minutiae of their own experiments - gels, PCR, assays.  Noone appreciates the technical beauty of your Perl or your MySQL table design.  You know all of the tools but increasingly, your focus is on how they work, not what to do with them.  Conversely, the people who should know what to do with them have no suggestions because they don't know the tools.  So you begin to wonder if you mightn't as well be working in telecommunications or sysadmin.

Don't worry, this afflicts us all.  And you have answered your own question - bioinformatics is just a bunch of tools.  It only works when they are applied to interesting scientific questions.

Ideally, there would be synergy between the wetlab people and the computer guy.  My experience is that this can be a problem and so you have to do twice the work - have the great scientific ideas and learn the computational tools.  Again, I think you have found the solution:  (1) network with people who do have interesting questions and (2) keep abreast of the literature and the types of problem that you find interesting and would like to answer.  It's also worth thinking about the other direction - which of my computational predictions could easily be validated in the lab with little work, perhaps as a student project or similar?</description>
		<content:encoded><![CDATA[<p>I think this post identifies a key problem of being &#8220;the computer guy&#8221; in a biological department.  It&#8217;s easy to fall into a kind of IT support role.  You keep the servers running, install software for people, write little scripts to analyse data for colleagues.  It&#8217;s hard to interact with your peers, most of whom are wrapped up in the minutiae of their own experiments - gels, PCR, assays.  Noone appreciates the technical beauty of your Perl or your MySQL table design.  You know all of the tools but increasingly, your focus is on how they work, not what to do with them.  Conversely, the people who should know what to do with them have no suggestions because they don&#8217;t know the tools.  So you begin to wonder if you mightn&#8217;t as well be working in telecommunications or sysadmin.</p>
<p>Don&#8217;t worry, this afflicts us all.  And you have answered your own question - bioinformatics is just a bunch of tools.  It only works when they are applied to interesting scientific questions.</p>
<p>Ideally, there would be synergy between the wetlab people and the computer guy.  My experience is that this can be a problem and so you have to do twice the work - have the great scientific ideas and learn the computational tools.  Again, I think you have found the solution:  (1) network with people who do have interesting questions and (2) keep abreast of the literature and the types of problem that you find interesting and would like to answer.  It&#8217;s also worth thinking about the other direction - which of my computational predictions could easily be validated in the lab with little work, perhaps as a student project or similar?</p>
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