Background: Quantitative models for transcriptional regulation have shown great promise for advancing our understanding of the biological mechanisms underlying gene regulation. Ho...
Denis C. Bauer, Fabian A. Buske, Timothy L. Bailey
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
We develop a new framework for inferring models of transcriptional regulation. The models in this approach, which we call physical models, are constructed on the basis of verifiab...
— Our paper presents a fully automated computational mechanism for targeting a space-variant retina based on the highlevel visual content of a scene. Our retina’s receptive fie...
Microarray technology produces large amounts of information to be manipulated by analysis methods, such as biclustering algorithms, to extract new knowledge. All-purpose multivaria...