Publication: Protein-protein functional association prediction using genetic programming
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2008
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Association for Computing Machinery (ACM)
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Abstract
Determining if a group of proteins are functionally associated among themselves is an open problem in molecular biology. Within our long term goal of applying Genetic Programming (GP) to this domain, this paper evaluates the feasibility of GP to predict if a given pair of proteins interacts. GP has been chosen because of its potential flexibility in many aspects, such as the definition of operations. In this paper, the if-unknown operation is defined, which semantically is the most appropriate in this domain for handling missing values. We have also used the Tarpeian bloat control method to decrease the computational time and the solution size. Our results show that GP is feasible for this domain and that the Tarpeian method can obtain large improvements in search efficiency and interpretability of solutions.
Description
Genetic and Evolutionary Computation Conference, GECCO-08. July 12-16, 2008, Atlanta, Georgia, USA.
Keywords
Algorithms, Measurement, Performance, Experimentation
Bibliographic citation
GECCO '08 : Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation, pp.347-348.