MSFO 2013 - Special Session on Multi-source Fusion in Omics

Technological advances in biological data acquisition and collection in the past two decades have resulted in a vast amount of biological data. The availability of these exponentially-growing omics datasets brings up the challenge to integrate information from multiple sources in a unified framework in bioinformatics. Recent work in bioinformatics benefits from integration of heterogeneous biological datasets including genomic, proteomic, transcriptomic, metabolomic and interactomic data in order to make more accurate inferences. New data mining and machine learning techniques built for integration of omics datasets can lead to new insights into biological domain.