Deciphering the signal transduction in normal cells and cancer cells is an essential step in curing cancer. In spite of its importance, understanding of the human signaling pathways is very limited. In fact, predicting the regulatory relationship between kinases/ phosphatases and transcription factors remains an extremely difficult problem. The methodology proposed in this study with hetero-regulatory similarity score and the hetero-regulatory module attempts to solve this problem. Our results demonstrate that signal transduction can be accurately recapitulated by a multilevel analysis of large-scale datasets. Although this study is conducted and tested in the model organism S.cerevisiae, we suppose that this method can be easily exploited in other organisms when the **data** becomes available. Currently, the binding specificity of many transcription factors has been studied through ChIP-chip and ChIP-seq experiments in human. With the recent development in RNAi technology, the construction of kinase/phosphatase single mutation cell lines and genome-wide measurement of gene expression level in these cell lines will be straightforward. Thus, our approach serves as a promising tool for the discovery of signaling pathways in human.