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T. Przytycka’s Research Group
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Teresa M. Przytycka’s
research group
Algorithmic and Graph Theoretical
methods in
Computational and Systems Biology
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Decomposition of Overlapping Protein Complexes
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Group members:
Elena
Zotenko
Katia S. Guimaraes
Raja
Jothi,
Teresa M. Przytycka
Elena Zotenko, Katia S. Guimaraes, Raja Jothi, Teresa M. Przytycka
Decomposition of Overlapping Protein Complexes: A Graph
Theoretical Method for Analyzing Static and Dynamic Protein Associations
BMC Algorithms for
Molecular Biology, 2006 1:7 (26 April 2006) pdf
Preliminary version presented at:
Elena Zotenko, Katia S.
Guimaraes, Raja Jothi, Teresa M.
Przytycka
Decomposition of Overlapping Protein Complexes: A Graph
Theoretical Method for Analyzing Static and Dynamic Protein Associations.
RECOMB2005 Satellite Meeting on Systems Biology.
Lecture Notes in Computational Biology Vol 4023 p 23-38.
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Background:
Most cellular processes are carried out by multi-protein complexes, groups
of proteins that bind together to perform a specific task. Some proteins
form stable complexes, while other proteins form transient
associations and are part of several complexes at different stages of a
cellular process. A better understanding of this higher-order organization
of proteins into overlapping complexes is an important step towards
unveiling functional and evolutionary mechanisms behind biological
networks.
Results: We propose a new method for identifying
and representing overlapping protein complexes (or larger units called
functional groups within a protein interaction network. We develop a
graph-theoretical framework that enables automatic construction of such
representation. We illustrate the effectiveness of our method by applying
it to TNF-alpha/NF-kappa-B and pheromone signaling pathways.
Conclusions: The proposed representation helps in understanding the transitions
between functional groups and allows for tracking a protein's path through
a cascade of functional groups. Therefore, depending on the nature of the
network, our representation is capable of elucidating temporal relations between
functional groups. Our results show that the proposed method opens a new
avenue for the analysis of protein interaction networks.
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