Unsupervised Extraction of Stable Expression Signatures from Public Compendia with an Ensemble of Neural Networks

Unsupervised Extraction of Stable Expression Signatures from Public Compendia with an Ensemble of Neural Networks

Cross-experiment comparisons in public data compendia are challenged by unmatched conditions and technical noise. The ADAGE method, which performs unsupervised integration with denoising autoencoder neural networks, can identify biological patterns, but because ADAGE models, like many neural network...

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Bibliographic Details
Main Authors: Tan, Jie, Doing, Georgia, Lewis, Kimberley A., Price, Courtney E., Chen, Kathleen M., Hogan, Deborah A., Greene, Casey S., Cady, Kyle, Perchuk, Barrett, Laub, Michael T
Other Authors: Massachusetts Institute of Technology. Department of Biology
Format: Article
Published: Elsevier BV 2018
Online Access:http://hdl.handle.net/1721.1/116746
https://orcid.org/0000-0002-8288-7607

Internet

http://hdl.handle.net/1721.1/116746
https://orcid.org/0000-0002-8288-7607

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