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Paper Details

Unsupervised feature construction and knowledge extraction from genome-wide assays of breast cancer with denoising autoencoders.
Pac Symp Biocomput
68
2015
DAs, ENCODE, ER, FOXM1, autoencoder, breast cancer, estrogen, estrogen receptor, molecular subtypes, normal samples, patient, tumor
Algorithms, Breast Neoplasms, Computational Biology, Databases, Genetic, Female, Genome-Wide Association Study, Genomics, Humans, Knowledge Bases, Prognosis, Receptors, Estrogen, Signal Transduction, Survival Analysis, Unsupervised Machine Learning
Author NameAffiliation
Jie TanInstitute for Quantitative Biomedical Sciences, Norris Cotton Cancer Center, The Geisel School of Medicine at Dartmouth
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Datasets

Release 1.2