Understanding the mechanism of complex human diseases is a major scientitic challenge. Towards this end, we developed a web-based network tool named iBIG （stands for integrative BioloGy）, which incorporates a variet...Understanding the mechanism of complex human diseases is a major scientitic challenge. Towards this end, we developed a web-based network tool named iBIG （stands for integrative BioloGy）, which incorporates a variety of information on gene interaction and regulation. The generated network can be annotated with various types of information and visualized directly online. In addition to the gene networks based on physical and pathway interactions, networks at a functional level can also be constructed. Furthermore, a supplementary R package is provided to process microarray data and generate a list of important genes to be used as input for iBIG. To demonstrate its usefulness, we collected 54 microarrays on common human diseases including cancer, neurolog- ical disorders, infectious diseases and other common diseases. We processed the microarray data with our R package and constructed a network of functional modules perturbed in common human diseases. Networks at the functional level in combination with gene networks may provide new insight into the mechanism of human diseases, iBIG is freely available at http：//lei.big.ac.cn/ibig.展开更多
基金supported by research grants from National Institute of Health to YD(Grant No. GM79383 and GM67168)Natural Science Foundation of China to HL(Grant No.30870474)Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry to HL
文摘Understanding the mechanism of complex human diseases is a major scientitic challenge. Towards this end, we developed a web-based network tool named iBIG （stands for integrative BioloGy）, which incorporates a variety of information on gene interaction and regulation. The generated network can be annotated with various types of information and visualized directly online. In addition to the gene networks based on physical and pathway interactions, networks at a functional level can also be constructed. Furthermore, a supplementary R package is provided to process microarray data and generate a list of important genes to be used as input for iBIG. To demonstrate its usefulness, we collected 54 microarrays on common human diseases including cancer, neurolog- ical disorders, infectious diseases and other common diseases. We processed the microarray data with our R package and constructed a network of functional modules perturbed in common human diseases. Networks at the functional level in combination with gene networks may provide new insight into the mechanism of human diseases, iBIG is freely available at http：//lei.big.ac.cn/ibig.
