Title
Using epigenetic networks for the analysis of movement associated with levodopa therapy for Parkinson's disease.
Abstract
Levodopa is a drug that is commonly used to treat movement disorders associated with Parkinson's disease. Its dosage requires careful monitoring, since the required amount changes over time, and excess dosage can lead to muscle spasms known as levodopa-induced dyskinesia. In this work, we investigate the potential for using epiNet, a novel artificial gene regulatory network, as a classifier for monitoring accelerometry time series data collected from patients undergoing levodopa therapy. We also consider how dynamical analysis of epiNet classifiers and their transitions between different states can highlight clinically useful information which is not available through more conventional data mining techniques. The results show that epiNet is capable of discriminating between different movement patterns which are indicative of either insufficient or excessive levodopa.
Year
DOI
Venue
2016
10.1016/j.biosystems.2016.05.005
Biosystems
Keywords
Field
DocType
Epigenetics,Artificial gene regulatory networks,epiNet,Classification,Parkinson's disease
Parkinson's disease,Neuroscience,Disease,Movement disorders,Biology,Neurology,Levodopa,Dyskinesia,Gene regulatory network,Epigenetics
Journal
Volume
ISSN
Citations 
146
0303-2647
1
PageRank 
References 
Authors
0.37
14
8
Name
Order
Citations
PageRank
Alexander P. Turner1344.72
Michael A. Lones216820.42
Martin A. Trefzer35212.24
Stephen L Smith4116383.01
D. R. Stuart Jamieson5354.17
Jane E. Alty6377.58
Jeremy Cosgrove742.81
Andy M. Tyrrell862973.61