Modular Multi-Relational Framework for Gene Group Function Prediction

Abstract. Determining the functions of genes is essential for under-standing how the metabolisms work, and for trying to solve their mal-functions. Genes usually work in groups rather than isolated, so functions should be assigned to gene groups and not to individual genes. Moreover, the genetic knowledge has many relations and is very frequently change-able. Thus, a propositional ad-hoc approach is not appropriate to deal with the gene group function prediction domain. We propose the Modu-lar Multi-Relational Framework (MMRF), which faces the problem from a relational and flexible point of view. The MMRF consists of several modules covering all involved domain tasks (grouping, representing and learning using computational prediction techniques). A specific applica-tion is described, including a relational representation language, where each module of MMRF is individually instantiated and refined for ob-taining a prediction under specific given conditions