title: A probabilistic approach to microRNA-target binding.
abstract: Elucidation of microRNA activity is a crucial step in understanding gene regulation. One key problem in this effort is how to model the pairwise interactions of microRNAs with their targets. As this interaction is strongly mediated by their sequences, it is desired to set-up a probabilistic model to explain the binding preferences between a microRNA sequence and the sequence of a putative target. To this end, we introduce a new model of microRNA-target binding, which transforms an aligned duplex to a new sequence and defines the likelihood of this sequence using a Variable Length Markov Chain. It offers a complementary representation of microRNA-mRNA pairs for microRNA target prediction tools or other probabilistic frameworks of integrative gene regulation analysis. The performance of present model is evaluated by its ability to predict microRNA-target mRNA interaction given a mature microRNA sequence and a putative mRNA binding site. In regard to classification accuracy, it outperforms two recent methods based on thermodynamic stability and sequence complementarity. The experiments can also unveil the effects of base pairing types and non-seed region in duplex formation.
authors.affiliation: Department of Computer Engineering, Başkent University, Bağlıca TR-06810, Ankara, Turkey. hogul@baskent.edu.tr
authors.forename: Hasan
authors.initials: H
authors.lastname: Oğul
authors.forename: Sinan U
authors.initials: SU
authors.lastname: Umu
authors.forename: Y Yener
authors.initials: YY
authors.lastname: Tuncel
authors.forename: Mahinur S
authors.initials: MS
authors.lastname: Akkaya
mesh_terms: D003198:Computer Simulation; D035683:MicroRNAs / Q000737:chemistry*; D008956:Models, Chemical; D011336:Probability; D012333:RNA, Messenger / Q000737:chemistry*
chemical_list: D035683:MicroRNAs; D012333:RNA, Messenger