中国邮电高校学报(英文) ›› 2007, Vol. 14 ›› Issue (1): 80-84.doi: 1005-8885 (2007) 01-0080-05
• Artificial Intelligence • 上一篇 下一篇
ZHANG Hong-xin, LU Ying-hua, ZHANG Jin-ling
ZHANG Hong-xin, LU Ying-hua, ZHANG Jin-ling
摘要:
Hierarchical clustering algorithms, such as Pearson’s correlation, Euclidean distance, Euclidean distance harmonic, Spearman rank correlation, Kendall’s tau, and City-block distance, were used to find the best way to establish theoretical MAPK/Erk signaling pathway on the basis of breast cancer line MCF-7 gene expressions. The algorithm constructs a hierarchy from top to bottom on the basis of a self-organizing tree. It dynamically finds the number of clusters at each level. It was found that only Euclidean distance harmonic is fit for the analysis of the cascade composed from a RAF1 (c-Raf), a MKNK1, a MAPKK (MEK1/2) to MAPK (Erk) in breast cancer line MCF-7. The result is consistent with the biological experimental MAP/Erk signaling pathway, and the theoretical MAPK/Erk signaling pathway on breast cancer line MCF-7 is set up.
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