Feature representation mathematically characterizes domain entities, which is crucial in machine learning. We designed a dynamic deep model to evaluate the over-representation of a disease and genes as the controlled vocabulary, with leveraging the contexture information with the word embedding and the global enrichment information, to represent the human diseases. The model has been evaluated and demonstrated the good fitness for predicting the associations of complex diseases. Authors: Guocai Chen, Herbert Chen, Yuntao Yang, Abhisek Mukherjee, Shervin Assassi, Claudio Soto, and Wenjin Zheng
