In this paper Hidden Markov Model algorithms are considered as a method for computing conditional properties of continuous-time stochastic simulation models. The goal is to develo...
Fabian Wickborn, Claudia Isensee, Thomas Simon, Sa...
Background: In order to improve gene prediction, extrinsic evidence on the gene structure can be collected from various sources of information such as genome-genome comparisons an...
The knowledge of the state sequences that explain a given observed sequence for a known hidden Markovian model is the basis of various methods that may be divided into three categ...
In this paper, we propose a general two-dimensional hidden Markov model (2D-HMM), where dependency of the state transition probability on any state is allowed as long as causality...