A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
Automated software customization is drawing increasing attention as a means to help users deal with the scope, complexity, potential intrusiveness, and ever-changing nature of mod...
Background: Discovering the genetic basis of common genetic diseases in the human genome represents a public health issue. However, the dimensionality of the genetic data (up to 1...
Raphael Mourad, Christine Sinoquet, Philippe Leray
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Bayesian network structure learning is a useful tool for elucidation of regulatory structures of biomolecular pathways. The approach however is limited by its acyclicity constraint...
S. Itani, Karen Sachs, Garry P. Nolan, M. A. Dahle...