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...
Recently, several algorithms have been proposed for using neural networks in dynamic analysis of small structural systems, and also constructing adaptive material modeling subrout...
Background: The fundamental role that intrinsic stochasticity plays in cellular functions has been shown via numerous computational and experimental studies. In the face of such e...
Asawari Samant, Babatunde A. Ogunnaike, Dionisios ...
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
The application of network analysis to emergent mating topologies in spatially structured genetic algorithms is presented in this preliminary study as a framework for inferring ev...