We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
Modeling in systems biology is concerned with using experimental information and mathematical methods to build quantitative models at different biological scales. This requires int...
Zhouyang Sun, Anthony Finkelstein, Jonathan Ashmor...
We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
A data simulator that can facilitate the development of improved sampling and analysis procedures for spatial analysis is proposed. The simulator, implemented in MATLAB, provides ...