Exploring Biopathways Related to Cancer Based on Differences of Gene Expression between Cancer and Normal Situation

Biopathway is one of the most important biological processes in living organisms. The works nowadays for prediction or reconstruction of pathway rely on computational approaches with genomics and proteomics information. However, even though the fact, the utility of whole-genomics and large-scale proteomics is still limited. It’s difficult to find a meaningful pathway in the enormous protein-protein interaction (PPI) network. On the other hand, gene expression is more appropriate for the regulation of pathway than PPI only. We propose an integrated method of gene expression and PPI for inferring potential fragment of pathway from strength of gene expression’s change. Meanwhile, we will develop a tool for this study and apply several cancer data to perform it. Results from our method will be compared with other pathway-prediction methods (shortest-path algorithm, NetSearch…etc.). This study could show that a pathway prediction from changes of gene expression could generate more biological significant results.