Revealing Disease Related Interactions by Correlation Analysis
The computational identification of disease related lesions is still a key open problem in biomedicine and systems biology. Dysregulated interactions may be an important reason that causes disease. In this paper, we aim to identify dysregulated interactions so as to elucidate the mechanism of disease in a systematic manner. Specially, we present a method to detect which protein-protein interactions or genetic interactions are downregulated or upregulated due to disease process. The proposed method was applied to a human molecular interaction network and a prostate cancer microarray dataset to reveal dysregulated interactions. The enrichment analysis of cancerous genes and disease related GO terms in identified dysregulated interactions shows that the identified dysregulated interactions are disease related, which verifies the effectiveness of our method.
Network Disease Interaction Correlation
Zi-Kai Wu Zhi-Yong Zhang Lv-Wen Zhang Katsuhisa Horimoto
Institute of Systems Biology, Shanghai University, Shanghai 200444 School of Communication and Infor Institute of Systems Biology, Shanghai University, Shanghai 200444 School of Computer Engineering an Computational Biology Research Center, National Institute of Advanced Industrial Science and Technol
国际会议
The Second International Symposium(OSB08)(第二届国际优化及系统生物学学术会议)
云南丽江
英文
341-349
2008-10-31（万方平台首次上网日期，不代表论文的发表时间）