Structure Elucidation And Confirmation In Plant Metabolomics: Novel Approaches Exemplified With Acyclic Diterpene Gylcosides | 2799
Journal of Computer Science & Systems Biology
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Protein-protein interaction (PPI) networks are
embedded with vital information about proteins?
functions. Analysis of PPI networks associated with
specific disease systems including cancer helps us
in the understanding of the complex biology of the
diseases. Specifically, identification of the similar and
distinct subgraphs across PPI networks will provide
useful clues on functional modules involved in the
diseases. In this study, we compared PPI networks
associated with 9 cancer diseases to identify their
common and distinct functional modules. We used
gene lists from Oncomine database and mapped them
against known interacting proteins to build cancer-
specific PPI networks. Subgraphs are abstracted to
patterns based on their graph topology and nodes?
properties. From these networks we discovered
frequent patterns that occur in all networks and at
each sub-graph size level. These patterns represent
the common functional modules of cancer diseases.
The distinct patterns are those appearing only in
a specific network and they represent functional
modules that are characteristic of a given cancer
type. We believe that this work would allow us to
identify functionally-relevant subgraphs in cancer
networks which can be advanced to experimental
validation to further our understanding of the
complex biology of cancer.
Dr. Chittibabu (Babu) Guda is the Director of Center for Bioinformatics and Systems Biology and an Associate Professor in the
department of Genetics, Cell Biology and Anatomy at the University of Nebraska Medical Center. He completed his Ph.D. from Auburn
University, and post-doctoral training from University of California at San Diego. He has published over 40 research articles in reputed
journals, and serving as an editorial board member for peer-reviewed journals and as a panelist for grant reviewing. His research
interests lie in the area of Computational Systems Biology, particularly on protein-protein and domain-domain interaction networks and
protein subcellular localization.
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