Integrating multiple sources of genomic data by multiplex network reconstruction

In recent years, rapidly accumulating genomic data have posed a challenge to integrate multiple data sources and to analyze the integrated networks globally. In this paper we present a method to reverse engineer integrative gene networks. The main advantage of our method is the integration of different quantitative and qualitative data sets in order to reconstruct a multiplex network, without necessarily imposing data constraints, such as each genomic datum needs to have the same number of entities. The computation boils down to solving small quadratic programs based on local neighborhood of nodes. We applied the method to DREAM5 dataset, and compared the results with the community networks from the challenge. We further demonstrated our method through a case study using breast cancer data, integrating metastasis gene expression data with interactome data. Overall, our method can be applied in many settings of network system biology.