An artificial neural network method for combining gene prediction based on equitable weights

Authors:
You Zhou;Yanchun Liang;Chengquan Hu;Liupu Wang;Xiaohu Shi
Affiliations:
College of Computer Science and Technology, Jilin University, Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Changchun, Jilin 130012, China;College of Computer Science and Technology, Jilin University, Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Changchun, Jilin 130012, China;College of Computer Science and Technology, Jilin University, Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Changchun, Jilin 130012, China;College of Computer Science and Technology, Jilin University, Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Changchun, Jilin 130012, China;College of Computer Science and Technology, Jilin University, Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Changchun, Jilin 130012, China
Venue:
Neurocomputing
Year:
2008

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Abstract

Gene prediction is still an important step to annotate genomes. In this paper, we proposed a novel method for recognizing gene in genomes. The method combines three famous gene-finding programs. After calculating the accuracy parameters, the equitable weight for each parameter is calculated using genetic algorithm. Then the integrative evaluation is performed. The integrative evaluation is employed to instruct the training of an artificial neural network. The simulation results show that the proposed method integrates advantages of three programs and the accuracy has an obvious improvement, which indicate that the proposed method has a powerful capability for gene prediction.