RIDDLE: reflective diffusion and local extension reveal functional associations for unannotated gene sets via proximity in a gene network
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The growing availability of large-scale functional networks has promoted the development of many successful techniques for predicting functions of genes. Here we extend these network-based principles and techniques to functionally characterize whole sets of genes. We present RIDDLE (Reflective Diffusion and Local Extension), which uses well developed guilt-by-association principles upon a human gene network to identify associations of gene sets. RIDDLE is particularly adept at characterizing sets with no annotations, a major challenge where most traditional set analyses fail. Notably, RIDDLE found microRNA-450a to be strongly implicated in ocular diseases and development. A web application is available at http://www.functionalnet.org/RIDDLE webcite.
Peggy I Wang12†, Sohyun Hwang3†, Rodney P Kincaid24, Christopher S Sullivan24, Insuk Lee3* and Edward M Marcotte25* Author Affiliations 1 Department of Biomedical Engineering, The University of Texas at Austin, 2500 Speedway, Austin, TX 78712, USA 2 Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712, USA 3 Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-749, Korea 4 Molecular Genetics and Microbiology, College of Natural Sciences, University of Texas at Austin, 2506 Speedway, Austin, TX 78712, USA 5 Department of Chemistry and Biochemistry, University of Texas at Austin, 2500 Speedway, Austin, TX 78712, USA