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Document NameResearch Thrust(not changed)
Creation time7/31/06 3:07:16 PM7/31/06 3:18:58 PM
Created byKaren(Lujie) ChenKaren(Lujie) Chen
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<h2>Life Science Data Mining</h2>
 
<p>Life sciences is a collective term encompassing biochemistry, genetics,
ecology, pharmacology, medicine, and many other sciences concerned with living
organisms.  The Auton Lab has diverse experience in data mining applications for
these disciplines, from core areas like drug discovery and drug classification,
to big-picture problems in epidemiology and pathogen detection.</p>
 
<p>Medicinal drugs are typically created through a process similar to Edison's
work on the light-bulb: very smart scientists think very hard about the desired
effect of a drug, then work very hard to limit their ideas to those few they can
afford to carefully test.  An alternative methodology is High Throughput
Screening (HTS), where truly enormous libraries of drug candidates are tested
for efficacy in robotic chemistry labs.  Modern HTS labs might make only 1
mistake in 1,000 experiments, but this leads to hundreds of mistakes on a small
HTS library -- roughly the same order of magnitude as the number of useful
chemicals in the library.</p>
 
<p>Detecting mistakes in HTS data can save hundreds or thousands of hours of
expensive wet lab time, as well as recover wrongly-disqualified candidates for
further testing.  This is a job for fast, robust, and correct statistics.  When
traditional statistical software packages failed to scale-up to the demands, the
Auton Lab developed new algorithms that met the challenge.  Beyond the research,
the Auton Lab delivered custom software libraries and user interfaces to our
collaborators, to help them make use of our algorithmic innovations.</p>
 
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<pre class="query">select name, summary where $tags = 'Life Science Data Mining' and documentType = 'Paper' and InCollection('autonweb') and branch = 'main' and language = 'en' order by name ASC
<pre class="query">select name,%AuthorsPart.content where $tags = 'Life Science Data Mining' and documentType = 'Paper' and InCollection('autonweb') and branch = 'main' and language = 'en' order by name ASC
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<p>
<a href="http://www.autonlab.org/auton_intranet/16605.html?branch=1&amp;language=2">Back</a>
</p>
 
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