Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
We present an approach to keyhole plan recognition which uses a dynamic belief (Bayesian) network to represent features of the domain that are needed to identify users’ plans and...
David W. Albrecht, Ingrid Zukerman, Ann E. Nichols...
Background: With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few appro...
Grace S. Shieh, Chung-Ming Chen, Ching-Yun Yu, Jui...
Background: RNA structure prediction problem is a computationally complex task, especially with pseudo-knots. The problem is well-studied in existing literature and predominantly ...
S. P. T. Krishnan, Sim Sze Liang, Bharadwaj Veerav...
The protein-protein interaction networks of even well-studied model organisms are sketchy at best, highlighting the continued need for computational methods to help direct experim...