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

ABSTRACT:

Motivation

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.

Results

We hypothesized that rat and human cells share a common signal-encoding mechanism but employ different proteins to transmit signals, and we developed a bimodal deep belief network and a semi-restricted bimodal deep belief network to represent the common encoding mechanism and perform trans-species learning. These 'deep learning' models include hierarchically organized latent variables ca

SUBMITTER: Chen L 

PROVIDER: S-EPMC4668779 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature