Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing data

Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing data

Abstract Background Deep learning has emerged as a versatile approach for predicting complex biological phenomena. However, its utility for biological discovery has so far been limited, given that generic deep neural networks provide little insight into the biological mechanisms that underlie a succ...

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Bibliographic Details
Main Authors: Nikolaus Fortelny, Christoph Bock
Format: Article
Language:English
Published: BMC 2020-08-01
Series:Genome Biology
Subjects:
Deep learning
Artificial neural networks
Single-cell sequencing
Gene regulation
Cell signaling networks
Functional genomics
Online Access:http://link.springer.com/article/10.1186/s13059-020-02100-5

Internet

http://link.springer.com/article/10.1186/s13059-020-02100-5

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