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  <event:Event rdf:about="http://ebiquity.umbc.edu/event/html/id/224/FALCON-Zero-in-on-the-Native-Protein-Structure">
    <rdfs:label><![CDATA[FALCON: Zero in on the Native Protein Structure]]></rdfs:label>
    <event:title><![CDATA[FALCON: Zero in on the Native Protein Structure]]></event:title>
    <event:speaker><person:Collaborator rdf:about="http://ebiquity.umbc.edu/person/html/Ming/Li/"><person:name><![CDATA[Ming  Li]]></person:name><rdfs:label><![CDATA[Ming  Li]]></rdfs:label></person:Collaborator></event:speaker>
    <event:startDate rdf:datatype="&xsd;dateTime">2008-02-01T15:30:00-05:00</event:startDate>
    <event:endDate rdf:datatype="&xsd;dateTime">2008-02-01T16:30:00-05:00</event:endDate>
    <event:location><![CDATA[325b ITE]]></event:location>
    <event:abstract><![CDATA[Protein structure prediction has been a heuristic science.  From homology modeling, threading, to Monte Carlo fragment assembly, decoy clustering, selection, refinement, and consensus, there is no unified model or theory governing the complete process.
<p>
We believe the protein structure prediction problem will only be solved by a simple computational model.  We wish to find a single and simple mathematical model that encompasses all of above paradigms and that takes a sequence and converges to a near-native protein structure. We propose such a theory, integrating ideas from fragment assembly, hidden Markov model sampling, and Ramachandran basins.  Our initial implementation, FALCON, of this theory converges to near-native structures on short benchmark protein sequences, and produces significantly better protein structures than the best programs in this field.
<p>
Joint work with: Shuaicheng Li, Dongbo Bu, and Jinbo Xu.
]]></event:abstract>
    <event:tag><![CDATA[bioinformatics]]></event:tag>
    <event:tag><![CDATA[algorithms]]></event:tag>
    <event:host><person:AffiliatedFaculty rdf:about="http://ebiquity.umbc.edu/person/html/Yaacov/Yesha/"><person:name><![CDATA[Yaacov  Yesha]]></person:name><rdfs:label><![CDATA[Yaacov  Yesha]]></rdfs:label></person:AffiliatedFaculty></event:host>
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