Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Genetic algorithms for parameter estimation in mathematical modeling of glucose metabolism
Computers in Biology and Medicine
Neural network model for integration and visualization of introgressed genome and metabolite data
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Linked Metabolites: A tool for the construction of directed metabolic graphs
Computers in Biology and Medicine
Finding metabolic pathways using atom tracking
Bioinformatics
Foundations of Genetic Programming
Foundations of Genetic Programming
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
Computers in Biology and Medicine
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Searching metabolic pathways that relate two compounds is a common task in bioinformatics. This is of particular interest when trying, for example, to discover metabolic relations among compounds clustered with a data mining technique. Search strategies find sequences to relate two or more states (compounds) using an appropriate set of transitions (reactions). Evolutionary algorithms carry out the search guided by a fitness function and explore multiple candidate solutions using stochastic operators. In this work we propose an evolutionary algorithm for searching metabolic pathways between two compounds. The operators and fitness function employed are described and the effect of mutation rate is studied. Performance of this algorithm is compared with two classical search strategies. Source code and dataset are available at http://sourceforge.net/projects/sourcesinc/files/eamp/