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The Resource Understanding structure, function, and evolution of protein-protein interactions by computational modeling and analysis, by Nan Zhao

Understanding structure, function, and evolution of protein-protein interactions by computational modeling and analysis, by Nan Zhao

Creator
Author
Summary
Currently, with the growth of experimental structural data on protein-protein interactions and larger protein complexes, the trend in computational biology and structural bioinformatics is towards applying such resources to model and analyze structures, functions, and evolutions of PPIs. Nevertheless, due to the rapid growth of the number of experimental structures, it becomes necessary to introduce bioinformatics methodologies, which rely on the advanced machine learning and information retrieval techniques, capable of handling complex and massive structural data. The research in this dissertation introduces and develops several computational methodologies to understand PPI 3D structures. First, we introduced an alignment-free similarity measure to detect structural similar PPI interfaces. This approach is capable of finding similar PPI interfaces formed by non-related protein subunits. Second, applying our similarity measure for PPIs, we showed our ability to use feature based interface similarity to classify and retrieve similar interface structures efficiently. Third, we used a set of simple protein interface structural features to test the classification and scoring performances for docked protein complexes, by using supervised and semi-supervised learning. Fourth, we analyzed the conservation patterns of charged residues located in PPI interfaces on a sampled set of PPI data. Last, we processed a genome-wide analysis of alternative splicing (AS) effects on human PPIs
Language
eng
Work
Publication
Extent
1 online resource (xvi, 127 pages)
Note
  • "A Dissertation presented to the Faculty of the Graduate School University of Missouri-Columbia In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy."
  • Dissertation Supervisor: Dr. Dmitry Korkin and Dr. Chi-Ren Shyu
  • Includes vita
Instance
Label
Understanding structure, function, and evolution of protein-protein interactions by computational modeling and analysis
Title
Understanding structure, function, and evolution of protein-protein interactions by computational modeling and analysis
Statement of responsibility
by Nan Zhao
Creator
Author
Subject
Genre
Language
eng
Summary
Currently, with the growth of experimental structural data on protein-protein interactions and larger protein complexes, the trend in computational biology and structural bioinformatics is towards applying such resources to model and analyze structures, functions, and evolutions of PPIs. Nevertheless, due to the rapid growth of the number of experimental structures, it becomes necessary to introduce bioinformatics methodologies, which rely on the advanced machine learning and information retrieval techniques, capable of handling complex and massive structural data. The research in this dissertation introduces and develops several computational methodologies to understand PPI 3D structures. First, we introduced an alignment-free similarity measure to detect structural similar PPI interfaces. This approach is capable of finding similar PPI interfaces formed by non-related protein subunits. Second, applying our similarity measure for PPIs, we showed our ability to use feature based interface similarity to classify and retrieve similar interface structures efficiently. Third, we used a set of simple protein interface structural features to test the classification and scoring performances for docked protein complexes, by using supervised and semi-supervised learning. Fourth, we analyzed the conservation patterns of charged residues located in PPI interfaces on a sampled set of PPI data. Last, we processed a genome-wide analysis of alternative splicing (AS) effects on human PPIs
Cataloging source
MUU
http://library.link/vocab/creatorName
Zhao, Nan
Degree
Ph. D.
Dissertation note
Thesis
Dissertation year
2013.
Government publication
government publication of a state province territory dependency etc
Granting institution
University of Missouri--Columbia,
Illustrations
illustrations
Index
no index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • theses
  • bibliography
http://library.link/vocab/subjectName
  • Bioinformatics
  • Protein-protein interactions
Label
Understanding structure, function, and evolution of protein-protein interactions by computational modeling and analysis, by Nan Zhao
Instantiates
Publication
Contributor
Thesis advisor
Note
  • "A Dissertation presented to the Faculty of the Graduate School University of Missouri-Columbia In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy."
  • Dissertation Supervisor: Dr. Dmitry Korkin and Dr. Chi-Ren Shyu
  • Includes vita
Bibliography note
Includes bibliographical references (pages 115-126)
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier.
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Control code
872588594
Extent
1 online resource (xvi, 127 pages)
Form of item
online
Media category
computer
Media MARC source
rdamedia.
Media type code
  • c
Other physical details
illustrations.
Specific material designation
remote
System control number
(OCoLC)872588594
Label
Understanding structure, function, and evolution of protein-protein interactions by computational modeling and analysis, by Nan Zhao
Publication
Contributor
Thesis advisor
Note
  • "A Dissertation presented to the Faculty of the Graduate School University of Missouri-Columbia In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy."
  • Dissertation Supervisor: Dr. Dmitry Korkin and Dr. Chi-Ren Shyu
  • Includes vita
Bibliography note
Includes bibliographical references (pages 115-126)
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier.
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Control code
872588594
Extent
1 online resource (xvi, 127 pages)
Form of item
online
Media category
computer
Media MARC source
rdamedia.
Media type code
  • c
Other physical details
illustrations.
Specific material designation
remote
System control number
(OCoLC)872588594

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