A key challenge in applying kernel-based methods for discriminative learning is to identify a suitable kernel given a problem domain. Many methods instead transform the input data...
Abstract. Over the last decade several prediction methods have been developed for determining structural and functional properties of individual protein residues using sequence and...
Huzefa Rangwala, Christopher Kauffman, George Kary...
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Motivation: Array-based comparative genomic hybridization (arrayCGH) has recently become a popular tool to identify DNA copy number variations along the genome. These profiles are...