Factor Regression Combining Heterogeneous Sources of Information

We present a non-parametric Bayesian factor regression model that combines two heterogeneous sources of information: gene expression arrays and text from their corresponding PubMed abstracts. Our model approximates a pLSI style model and results in improved regression accuracy. We apply this model to gene-expression data analysis, but it is extendable to… CONTINUE READING