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Characterisation of movement disorder in parkinson's disease using evolutionary algorithms.

, , , , , , and . GECCO (Companion), page 1479-1486. ACM, (2013)

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Characterising neurological time series data using biologically motivated networks of coupled discrete maps., , , , and . Biosystems, 112 (2): 94-101 (2013)Discriminating normal and cancerous thyroid cell lines using implicit context representation Cartesian genetic programming., , , , , , and . IEEE Congress on Evolutionary Computation, page 1-6. IEEE, (2010)The evolutionary computation approach to motif discovery in biological sequences., and . GECCO Workshops, page 1-11. ACM, (2005)Classification and characterisation of movement patterns during levodopa therapy for parkinson's disease., , , , , and . GECCO (Companion), page 1321-1328. ACM, (2014)Metaheuristics in nature-inspired algorithms.. GECCO (Companion), page 1419-1422. ACM, (2014)Evolved Artificial Signalling Networks for the Control of a Conservative Complex Dynamical System., , , , , and . IPCAT, volume 7223 of Lecture Notes in Computer Science, page 38-49. Springer, (2012)Towards Intelligent Biological Control: Controlling Boolean Networks with Boolean Networks., , and . EvoApplications (1), volume 9597 of Lecture Notes in Computer Science, page 351-362. Springer, (2016)Instruction-level design of local optimisers using push GP.. GECCO (Companion), page 1487-1494. ACM, (2019)Evolving Classifiers to Recognize the Movement Characteristics of Parkinson's Disease Patients., , , , , , and . IEEE Trans. Evolutionary Computation, 18 (4): 559-576 (2014)2015 Information Processing in Cells and Tissues (IPCAT 2015)., , , and . Biosystems, (2016)