Machine Learning for Exploring State Space Structure in Genetic Regulatory Networks

Machine Learning for Exploring State Space Structure in Genetic Regulatory Networks

Genetic regulatory networks (GRN) offer a useful model for clinical biology. Specifically, such networks capture interactions among genes, proteins, and other metabolic factors. Unfortunately, it is difficult to understand and predict the behavior of networks that are of realistic size and complexit...

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Bibliographic Details
Main Author: Thomas, Rodney H.
Format: Others
Published: NSUWorks 2018
Subjects:
asynchronous Boolean networks
attractors
Boolean networks
cross-validation
decision trees
fuzzy basins
fuzzy membership vectors
fuzzy vectors
genetic regulatory networks
Markov Chain Monte Carlo
naïve Bayesian classifiers
support vector machines
Computer Sciences
Online Access:https://nsuworks.nova.edu/gscis_etd/1053
https://nsuworks.nova.edu/cgi/viewcontent.cgi?article=2040&context=gscis_etd

Internet

https://nsuworks.nova.edu/gscis_etd/1053
https://nsuworks.nova.edu/cgi/viewcontent.cgi?article=2040&context=gscis_etd

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