AutoOmics: New multimodal approach for multi-omics research

AutoOmics: New multimodal approach for multi-omics research

Deep learning is very promising in solving problems in omics research, such as genomics, epigenomics, proteomics, and metabolics. The design of neural network architecture is very important in modeling omics data against different scientific problems. Residual fully-connected neural network (RFCN) w...

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Bibliographic Details
Main Authors: Chi Xu, Denghui Liu, Lei Zhang, Zhimeng Xu, Wenjun He, Hualiang Jiang, Mingyue Zheng, Nan Qiao
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:Artificial Intelligence in the Life Sciences
Subjects:
Multi-omics
Cancer genomics
Integrative analysis
Automatic machine learning
Deep learning
Online Access:http://www.sciencedirect.com/science/article/pii/S266731852100012X

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http://www.sciencedirect.com/science/article/pii/S266731852100012X

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