Proceedings of the Korean Information Science Society Conference (한국정보과학회:학술대회논문집)
- 2002.10c
- /
- Pages.739-742
- /
- 2002
- /
- 1598-5164(pISSN)
Independent Feature Subspace Analysis for Gene Expression Data
유전자 발현 데이터의 독립 특징 부공간 해석
- Kim, Heijin (Dept. of CSE, Pohang University of Science & Technology) ;
- Park, Seungjin (Dept. of CSE, Pohang University of Science & Technology) ;
- Bang, Sung-Yang (Dept. of CSE, Pohang University of Science & Technology)
- Published : 2002.10.01
Abstract
This paper addresses a new statistical method, IFSAcycle, which is an unsupervised learning method of analyzing cell cycle-related gene expression data. The IFSAcycle is based on the independent feature subspace analysis (IFAS) [3], which generalizes the independent component analysis (ICA). Experimental results show the usefulness of IFAS: (1) the ability of assigning genes to multiple coexpression pattern groups; (2) the capability of clustering key genes that determine each critical point of cell cycle.
Keywords