Mining spatial association rules of multiple co-occurring motifs to discover cis-regulatory modules

Biological activities are typically co-regulated by several factors and this feature is properly reflected by higher-order structures called cis-regulatory modules (CRM) and represented by non-random clusters of regulatory motifs. Several methods have been proposed for the de novo discovery of modules. We propose an alternative approach based on the discovery of rules which define strong spatial associations between single motifs and suggest the structure of a module. Rules are expressed in a first-order logic formalism and are mined by means of an inductive logic programming (ILP) system. We also propose computational solutions to two issues: the hard discretization of numerical inter-motif distances and the choice of a minimum support threshold. All methods have been implemented and integrated in a prototypal tool designed to support biologists in the discovery and characterization of cis-regulatory modules.