Grammatical Immune System Evolution for Reverse Engineering Nonlinear Dynamic Bayesian Models

Grammatical Immune System Evolution for Reverse Engineering Nonlinear Dynamic Bayesian Models

Show other versions (1)

An artificial immune system algorithm is introduced in which nonlinear dynamic models are evolved to fi t time series of interacting biomolecules. This grammar-based machine learning method learns the structure and parameters of the underlying dynamic model. In silico immunogenetic mechanisms for the...

Full description

Bibliographic Details
Main Authors: B.A. McKinney, D. Tian
Format: Article
Language:English
Published: SAGE Publishing 2008-01-01
Series:Cancer Informatics
Subjects:
artificial immune system
somatic hypermutation
V(D)J recombination
unscented kalman filter
dynamic bayesian network
estrogen metabolism
nonlinear dynamic bayesian model
Online Access:http://www.la-press.com/article.php?article_id=983

Internet

http://www.la-press.com/article.php?article_id=983

Similar Items