title: RIDDLE: reflective diffusion and local extension reveal functional associations for unannotated gene sets via proximity in a gene network.
abstract: 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.
authors.forename: Peggy I
authors.initials: PI
authors.lastname: Wang
authors.forename: Sohyun
authors.initials: S
authors.lastname: Hwang
authors.forename: Rodney P
authors.initials: RP
authors.lastname: Kincaid
authors.forename: Christopher S
authors.initials: CS
authors.lastname: Sullivan
authors.forename: Insuk
authors.initials: I
authors.lastname: Lee
authors.forename: Edward M
authors.initials: EM
authors.lastname: Marcotte
mesh_terms: D000818:Animals; D005128:Eye Diseases / Q000235:genetics; D053263:Gene Regulatory Networks; D023281:Genomics / Q000379:methods; D006801:Humans; D051379:Mice; D035683:MicroRNAs / Q000378:metabolism; D058977:Molecular Sequence Annotation; D012984:Software
chemical_list: D035683:MicroRNAs