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Title: Integrating Protein Data Resources
through Semantic Web Services
When: November 7, 2006 10:00am – 12:00pm
Where: Room 522 IS Bldg.
Who: Xiong Liu
Committee:
Dr. Hassan Karimi (advisor), School of Information Sciences,
University of Pittsburgh
Dr. Michael Lewis, School of
Information Sciences, University of Pittsburgh
Dr. Vladimir
Zadorozhny, School of Information Sciences, University
of Pittsburgh
Dr. Ivet Bahar, Department of Computational
Biology, School of Medicine, University of Pittsburgh
Dr. John Vries, Department of Computational Biology,
School of Medicine, University of Pittsburgh
Abstract:Understanding the function
of every protein is one major objective of bioinformatics.
Currently, a large amount of information (e.g., sequence,
structure and dynamics) is being produced by experiments
and predictions that are associated with protein function.
Integrating these diverse data about protein sequence,
structure, dynamics and other protein features allows
further exploration and establishment of the relationships
between protein sequence, structure, dynamics and function,
and thereby controlling the function of target proteins.
However, information integration in protein data resources
faces challenges at technology level for interfacing
heterogeneous data formats and standards and at application
level for semantic interpretation of dissimilar data
and queries.
In this research, a semantic web services infrastructure,
called Web Services for Protein data resources (WSP),
for flexible and user-oriented integration of protein
data resources, is proposed. This infrastructure includes
a method for modeling protein web services, a service
publication algorithm, an efficient service discovery
(matching) algorithm, and an optimal service chaining
algorithm. Rather than relying on syntactic matching,
the matching algorithm discovers services based on their
similarity to the requested service. Therefore, users
can locate services that semantically match their data
requirements even if they are syntactically distinctive.
Furthermore, WSP supports a workflow-based approach for
service integration. The chaining algorithm is used to
select and chain services, based on the criteria of service
accuracy and data interoperability. The algorithm generates
a web services workflow which automatically integrates
the results from individual services.
A number of experiments are conducted to evaluate the
performance of the matching algorithm. The results reveal
that the algorithm can discover services with reasonable
performance. Also, a composite service, which integrates
protein dynamics and conservation, is experimented using
the WSP infrastructure.
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