title: Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning.
abstract: Knowing the sequence specificities of DNA- and RNA-binding proteins is essential for developing models of the regulatory processes in biological systems and for identifying causal disease variants. Here we show that sequence specificities can be ascertained from experimental data with 'deep learning' techniques, which offer a scalable, flexible and unified computational approach for pattern discovery. Using a diverse array of experimental data and evaluation metrics, we find that deep learning outperforms other state-of-the-art methods, even when training on in vitro data and testing on in vivo data. We call this approach DeepBind and have built a stand-alone software tool that is fully automatic and handles millions of sequences per experiment. Specificities determined by DeepBind are readily visualized as a weighted ensemble of position weight matrices or as a 'mutation map' that indicates how variations affect binding within a specific sequence.
authors.affiliation: 1] Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada. [2] Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada.
authors.forename: Babak
authors.initials: B
authors.lastname: Alipanahi
authors.affiliation: Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada.
authors.forename: Andrew
authors.initials: A
authors.lastname: Delong
authors.affiliation: 1] Canadian Institute for Advanced Research, Programs on Genetic Networks and Neural Computation, Toronto, Ontario, Canada. [2] Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA. [3] Divisions of Biomedical Informatics and Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
authors.forename: Matthew T
authors.initials: MT
authors.lastname: Weirauch
authors.affiliation: 1] Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada. [2] Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada. [3] Canadian Institute for Advanced Research, Programs on Genetic Networks and Neural Computation, Toronto, Ontario, Canada.
authors.forename: Brendan J
authors.initials: BJ
authors.lastname: Frey
mesh_terms: D019295:Computational Biology / Q000379:methods*; D004268:DNA-Binding Proteins / Q000737:chemistry*; D056510:Position-Specific Scoring Matrices; D016601:RNA-Binding Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software
chemical_list: D004268:DNA-Binding Proteins; D016601:RNA-Binding Proteins