title: Computational Prediction of microRNA Targets.
abstract: Computational prediction of microRNA (miRNA) targets is a fundamental step towards the characterization of miRNA function and the understanding of their role in disease. A single miRNA can regulate hundreds of different gene transcripts through partial sequence complementarity and a single gene may be regulated by several miRNAs acting cooperatively. The remarkable advances made in recent years have allowed the identification of key features for functional miRNA binding sites. A plethora of prediction tools are now available, but their accuracies remain rather poor, as miRNA target recognition has revealed itself to be a very complex and dynamic mechanism, still only partially understood.In this chapter, the principles of miRNA target prediction in animals are presented, together with the most up-to-date and effective computational approaches and tools available.
authors.affiliation: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L Levy Pl, New York, NY, 10029, USA. alessandro.lagana@mssm.edu.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Laganà
mesh_terms: D000818:Animals; D001483:Base Sequence; D001665:Binding Sites; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D023281:Genomics / Q000379:methods*; D035683:MicroRNAs / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D013816:Thermodynamics
chemical_list: D035683:MicroRNAs
keywords: Post-transcriptional gene regulation; Target prediction; microRNA