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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=protein">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=protein]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for protein]]></description>
  <items>
    <rdf:Seq>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/292/Stochastic-and-Iterative-Techniques-for-Relational-Data-Clustering"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/255/Domain-based-computational-approaches-to-understand-the-molecular-basis-of-diseases"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/224/FALCON-Zero-in-on-the-Native-Protein-Structure"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/82/High-Performance-Scientific-Computing-for-Large-Scale-Biomolecular-simulations-on-Blue-Gene-L-supercomputer"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/553/Sub-cellular-Feature-Detection-and-Automated-Extraction-of-Collocalized-Actin-and-Myosin-Regions"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/796/A-more-appropriate-Protein-Classification-using-Data-Mining"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/252/Domain-based-computational-approaches-to-understand-the-molecular-basis-of-diseases"/>
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 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/292/Stochastic-and-Iterative-Techniques-for-Relational-Data-Clustering">
  <title><![CDATA[Stochastic and Iterative Techniques for Relational Data Clustering]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/292/Stochastic-and-Iterative-Techniques-for-Relational-Data-Clustering</link>
  <description><![CDATA[Dissertation Defense


This research focuses on the topic of relational data clustering,
which is the task of organizing objects into logical groups, or
clusters, taking into account the relational links between objects. As
a research area, relational clustering has received a great deal of
attention recently, because of the large variety of social media
applications and other modern relational data sources that have become
popular, such as weblogs, protein interaction networks, soci...]]></description>
  <dc:date>2009-04-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/255/Domain-based-computational-approaches-to-understand-the-molecular-basis-of-diseases">
  <title><![CDATA[Domain-based computational approaches to understand the molecular basis of diseases]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/255/Domain-based-computational-approaches-to-understand-the-molecular-basis-of-diseases</link>
  <description><![CDATA[Protein domains, or domains, are the evolutionary, structural and
functional units of the proteins. Despite the obvious relevance of
domains to understanding biological process at the molecular level,
most high-throughput experimental data relating molecular information
to biological process, including diseases, is only analyzed at the
gene or protein level. I will introduce a new approach, the protein
domain profiling, to analyze clinical data derived from microarray and
other experim...]]></description>
  <dc:date>2008-09-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/224/FALCON-Zero-in-on-the-Native-Protein-Structure">
  <title><![CDATA[FALCON: Zero in on the Native Protein Structure]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/224/FALCON-Zero-in-on-the-Native-Protein-Structure</link>
  <description><![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.

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 ...]]></description>
  <dc:date>2008-02-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/82/High-Performance-Scientific-Computing-for-Large-Scale-Biomolecular-simulations-on-Blue-Gene-L-supercomputer">
  <title><![CDATA[High Performance Scientific Computing for Large Scale Biomolecular simulations on Blue Gene/L supercomputer]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/82/High-Performance-Scientific-Computing-for-Large-Scale-Biomolecular-simulations-on-Blue-Gene-L-supercomputer</link>
  <description><![CDATA[This talk will cover the following topics:

 

 History of the Blue Gene Program.

 Overview of the Blue Gene/L hardware and software

 Blue Matter application overview: A scalable Molecular Dynamics framework for Blue Gene/L supercomputer

 Blue Gene science overview:  Protein folding mechanisms, membrane bound systems etc.]]></description>
  <dc:date>2005-03-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/553/Sub-cellular-Feature-Detection-and-Automated-Extraction-of-Collocalized-Actin-and-Myosin-Regions">
  <title><![CDATA[Sub-cellular Feature Detection and Automated Extraction of Collocalized Actin and Myosin Regions]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/553/Sub-cellular-Feature-Detection-and-Automated-Extraction-of-Collocalized-Actin-and-Myosin-Regions</link>
  <description><![CDATA[We describe a new distance-based metric to measure the strength of collocalization in multi-color microscopy images for user-selected regions. This metric helps to standardize, objectify, quantify, and even automate light microscopy observations. Our new algorithm uses this metric to automatically identify and annotate a donut shaped actomyosin stress fiber bundle evident in vascular smooth muscle cells on certain types of surfaces. Both the metric and the algorithm have been implemented as a...]]></description>
  <dc:date>2012-01-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/796/A-more-appropriate-Protein-Classification-using-Data-Mining">
  <title><![CDATA[A more appropriate Protein Classification using Data Mining]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/796/A-more-appropriate-Protein-Classification-using-Data-Mining</link>
  <description><![CDATA[Research in bioinformatics is a complex phenomenon as it overlaps two knowledge domains, namely, biological and computer sciences. This paper has tried to introduce an efficient data mining approach for classifying proteins into some useful groups by representing them in hierarchy tree structure. There are several techniques used to classify proteins but most of them had few drawbacks on their grouping. Among them the most efficient grouping technique is used by PSIMAP. Even though PSIMAP (Pr...]]></description>
  <dc:date>2010-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/252/Domain-based-computational-approaches-to-understand-the-molecular-basis-of-diseases">
  <title><![CDATA[Domain-based computational approaches to understand the molecular basis of diseases]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/252/Domain-based-computational-approaches-to-understand-the-molecular-basis-of-diseases</link>
  <description><![CDATA[Protein domains, or domains, are the evolutionary, structural and functional units of the proteins. Despite the obvious relevance of domains to understanding biological process at the molecular level, most high-throughput experimental data relating molecular information to biological process, including diseases, is only analyzed at the gene or protein level. I will introduce a new approach, the protein domain profiling, to analyze clinical data derived from microarray and other experimental h...]]></description>
  <dc:date>2008-09-05</dc:date>
 </item>
</rdf:RDF>
