A deep neural network approach for learning intrinsic protein-RNA binding preferences
Author:
Affiliation:
1. Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel
2. Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel
Funder
Edmond J. Safra Center for Bioinformatics at Tel-Aviv University
Blavatnik Research Fund
Blavatnik Interdisciplinary Cyber Research Center in Tel-Aviv University
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability
Link
http://academic.oup.com/bioinformatics/article-pdf/34/17/i638/25702404/bty600.pdf
Reference50 articles.
1. Predicting the sequence specificities of DNA-and RNA-binding proteins by deep learning;Alipanahi;Nat. Biotechnol,2015
2. Deep learning for computational biology;Angermueller;Mol. Syst. Biol,2016
3. Continuous distributed representation of biological sequences for deep proteomics and genomics;Asgari;PloS One,2015
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