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       <td id="bannertd2" height="60" width="100%" border="0" align="center" valign="middle" background="images/bannermiddle.gif" nowrap="true"><h1 class="banner">Bioinformatics</h1></td>
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<table border="0"><tr><td valign="top"><span xmlns="" class="title">Putting it All Together: Integrating Omic Data Sets</span><br xmlns=""/><span xmlns="" class="source"><a href="http://agt-info.org" target="publications">Association of Genetic Technologists</a></span>,
       <span xmlns="" class="source"><a href="http://agt-info.org/2003AnnualMeeting.html" target="publications">June 6, 2003 </a></span><br/><span xmlns="" class="author">by <a href="http://www.houseofyin.com" target="publications">David Kane</a></span><p xmlns=""><span class="label">Abstract: </span><abstract>The explosion of high-throughput technologies to measure gene and protein expression on a genomic scale is
revolutionizing biology.  While the exploration of relationships within data sets are vital, much can be gained by
looking at the relationships between different types of data gathered on the same set of samples.  The NCI60, a
panel of 60 cell lines used by the NCI Developmental Therapeutics Program in the ongoing screening of chemical compounds
for anti-cancer activity, is one of the most extensively characterized sets of cell lines in the world.  Data exist for these
cells lines on the DNA, RNA, protein, functional and pharmacological levels.  These data can be analyzed in combination to
yield information relating molecular profiles to cellular phenotypes.  This talk focused on the challenges to integrating
these different data sets, and tools that can be used to address these challenges.
</abstract></p></td><td valign="top"/></tr></table>
     
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