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http://dx.doi.org/10.3745/KIPSTB.2006.13B.1.001

Modular neural network in prediction of protein function  

Hwang Doo-Sung (단국대학교 컴퓨터과학과)
Publication Information
The KIPS Transactions:PartB / v.13B, no.1, 2006 , pp. 1-6 More about this Journal
Abstract
The prediction of protein function basically make use of a protein-protein interaction map based on the concept of guilt-by-association. The method however cannot determine the functions of proteins in case that the target protein does not interact with proteins with known functions directly. This paper studies protein function prediction considering the given problem as a K-class classification problem and proposes a predictive approach utilizing a modular neural network. The proposed method uses interaction data and protein related attributes as well. The experimental results demonstrate that the proposed approach can predict the functional roles of Yeast proteins whose interaction knowledge is not known and shows better performance than the graph-based models that use protein interaction data.
Keywords
Modular Neural Network; Multi-class Classification; Proteomics; Protein Function Prediction;
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Times Cited By KSCI : 1  (Citation Analysis)
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