A KNN-Based learning method for biology species categorization

Authors:
Yan Dang;Yulei Zhang;Dongmo Zhang;Liping Zhao
Affiliations:
Computer Science and Engineering Department, Shanghai Jiao Tong University, Shanghai, P. R. China;School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, P. R. China;Computer Science and Engineering Department, Shanghai Jiao Tong University, Shanghai, P. R. China;School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, P. R. China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Year:
2005

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Using a generalized instance set for automatic text categorization

Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval

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Abstract

This paper presents a novel approach toward high precision biology species categorization which is mainly based on KNN algorithm. KNN has been successfully used in natural language processing (NLP). Our work extends the learning method for biological data. We view the DNA or RNA sequences of certain species as special natural language texts. The approach for constructing composition vectors of DNA and RNA sequences is described. A learning method based on KNN algorithm is proposed. An experimental system for biology species categorization is implemented. Forty three different bacteria organisms selected randomly from EMBL are used for evaluation purpose. And the preliminary experiments show promising results on precision.