Inspired by Bayesian inference, a more accurate coefficient-level zero-quantized threshold model in the RDO sense is proposed by fully simulating RDOQ to aid in the following AZB detection.
We start with a brief description of the original TR methods DR-FFL and TRANSWESD which inspired the novel inference algorithms presented herein.
In this study we use a statistical inference technique inspired by statistical physics, which builds a coevolutionary "Potts" Hamiltonian model of sequence variation in a protein family.
The method of network inference presented in this paper is inspired by the theory of time-lagged correlation inference with regard to the deduction of the interaction network, and on a maximum likelihood approach with regard to the estimation of the kinetic parameters of the network.
Neuro-fuzzy is a hybrid representation which combines the linguistic description typical of fuzzy inference systems, with learning procedures inspired by neural networks.
Rule (5) is modeled on the straight rule for enumerative induction and inspired by Mill's view of analogical inference, as described in §2.3.
We used WinBUGS for scripting this inference and our scripts were inspired by Adams et al. [ 30].
The network inference method we propose is inspired to the recent works of M. Samoilov et al. [ 16] and A. Arkin et al. [ 17] and has been tailored for pharamcokinetics-pharmacodynamic modelling.
Inspired by the success of ab initio inference of domains and diseases, we further propose the following application of the proposed domainRBF approach in the inference of genes that are associated with diseases, by combining predicted domain-disease associations and known domain-protein relations.
This paper considers them as an independent category because almost all of them are inspired by intelligent behaviors in nature such as inference, designing, thinking, and learning.
In this work, a multiobjective metaheuristic inspired by honey bees is applied to tackle the phylogenetic inference problem.
