Modeling in-vivo protein-DNA binding by combining multiple-instance learning with a hybrid deep neural network
Author:
Funder
China Postdoctoral Science Foundation
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
http://www.nature.com/articles/s41598-019-44966-x.pdf
Reference51 articles.
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2. Orenstein, Y. & Shamir, R. A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data. Nucleic acids research 42, e63–e63 (2014).
3. Furey, T. S. ChIP–seq and beyond: new and improved methodologies to detect and characterize protein–DNA interactions. Nature Reviews Genetics 13, 840–852 (2012).
4. Jothi, R., Cuddapah, S., Barski, A., Cui, K. & Zhao, K. Genome-wide identification of in vivo protein–DNA binding sites from ChIP-Seq data. Nucleic acids research 36, 5221–5231 (2008).
5. Stormo, G. D. Consensus patterns in DNA. Methods in enzymology 183, 211–221 (1990).
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