Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
Background: An increasing number of researchers have released novel RNA structure analysis and prediction algorithms for comparative approaches to structure prediction. Yet, indep...
As genomic and proteomic data is collected from highthroughput methods on a daily basis, subcellular components are identified and their in vitro behavior is characterized. Howev...
Salim Khan, William Gillis, Carl Schmidt, Keith De...
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Background: High-throughput mass spectrometry (MS) proteomics data is increasingly being used to complement traditional structural genome annotation methods. To keep pace with the...
William S. Sanders, Nan Wang, Susan M. Bridges, Br...