Abstract. With the availability of hundreds and soon-to-be thousands of complete genomes, the construction of genome-scale metabolic models for these organisms has attracted much a...
Prediction is emerging as an essential ingredient for real-time monitoring, planning and decision support applications such as intrusion detection, e-commerce pricing and automate...
Abstract. We describe a probabilistic model, implemented as a dynamic Bayesian network, that can be used to predict nucleosome positioning along a chromosome based on one or more g...
Sheila M. Reynolds, Zhiping Weng, Jeff A. Bilmes, ...
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...