Collaboration visualization on large dataset for protein-protein interaction network

The accumulation of huge amount of biology data and their heterogeneity has become a bottleneck in the analysis of protein-protein interaction (PPI) networks, especially in the visualization of PPI networks. Because the format of the data generated from different experimental groups is diverse, and the databases for the storage and management of the data are different, network visualization of the heterogeneous data by integrating different derived data is challenging and is a key to comprehensively understanding the mechanism of biology system. To visualize the interactions of proteins, we first utilize the robot crawl technique to dynamically integrate the information of protein-protein interactions from all the related public databases such as Protein Interaction Database (PID), Human Protein Reference Database (HPRD) and Reactome. Second, we use a graph algorithm to partition the complex network into different sub-networks to discover the `Hub´ proteins in the visualization protein-protein networks. Finally, we develop a protocol for the collaboration of different researchers based on the visualization of the PPI networks.