Computational Detectionfor Human Protein Interaction Networkin Cell Cycle Regulation

• Main Authors: Hui-Ping Chou, 周慧萍
• Other Authors: Jung-Hsien Chiang
• Format: Others
• Language: en_US
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/66086661113886105659

碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 91 === Protein-protein interactions (PPIs) play pivotal roles in various aspects of the structural and functional organization of the cell, and their complete description is indispensable to thorough understanding of the cell. The binary relationship between two proteins, protein-protein interaction, is the simplest unit of the complex biological process or pathway. Interaction network constructed by binary relationship of protein pairs depicts the global view of relationships among proteins and provide the insight of the complex biological process. Recently, large-scale two-hybrid screens have generated a wealth of information of PPIs for Saccharomyces cerevisiae (yeast). We propose an approach to deduce the PPIs in human from yeast by the homologous relationship. We choose the cell cycle related yeast proteins as the target of our approach. This work tempts to speculate potential interactions that may help in understanding the molecular mechanisms involved in human tumorigenesis. In addition to provide more evidences from different information resources, we evaluate the shared keywords from Swiss-Prot and co-occurrence of protein names from MEDLINE for the predicted PPIs. Finally, we verify the predicted PPIs in human with those in DIP (Database of Interacting Proteins). The result shows the sequence-based approach can be used globally to identify potential PPIs across species.