Trans-species learning of cellular signaling systems with bimodal deep belief networks | Zendy

Lujia Chen | Zendy; Chunhui Cai | Zendy; Vicky Chen | Zendy; Xinghua Lu | Zendy

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Trans-species learning of cellular signaling systems with bimodal deep belief networks

Author(s) -

Lujia Chen,

Chunhui Cai,

Vicky Chen,

Xinghua Lu

Publication year - 2015

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv315

Subject(s) - deep learning , computer science , mechanism (biology) , artificial intelligence , task (project management) , encoding (memory) , deep belief network , machine learning , drug discovery , systems biology , model system , computational biology , biology , bioinformatics , philosophy , management , epistemology , economics

Model organisms play critical roles in biomedical research of human diseases and drug development. An imperative task is to translate information/knowledge acquired from model organisms to humans. In this study, we address a trans-species learning problem: predicting human cell responses to diverse stimuli, based on the responses of rat cells treated with the same stimuli.

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