D
Don Kulasiri
Researcher at Canterbury of New Zealand
Publications - 137
Citations - 1217
Don Kulasiri is an academic researcher from Canterbury of New Zealand. The author has contributed to research in topics: Stochastic differential equation & Medicine. The author has an hindex of 18, co-authored 126 publications receiving 1050 citations. Previous affiliations of Don Kulasiri include American College of Surgeons & Lincoln University (New Zealand).
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Towards abstraction of computational modelling of mammalian cell cycle: Model reduction pipeline incorporating multi-level hybrid petri nets.
TL;DR: A model abstraction scheme/pipeline to create a minimal abstract model of the whole mammalian cell cycle system from a large Ordinary Differential Equation model of cell cycle, and shows that the MLHPN provides a close approximation to the comprehensive benchmark model in robustly representing systems dynamics and emergent properties.
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Synthesizing neurophysiology, genetics, behaviour and learning to produce whole-insect programmable sensors to detect volatile chemicals.
Glen C. Rains,Don Kulasiri,Zhongkun Zhou,Sandhya Samarasinghe,Jeffery K. Tomberlin,Dawn M. Olson +5 more
TL;DR: This review article examines how the neurophysiological, molecular, genetic and behavioural system of olfaction works and how an understanding of these systems should lead the way to future developments in whole-insect programmable sensors.
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Development of a behavior parameter in classically conditioned parasitic wasps that detect changes in odor intensity
TL;DR: A method of foraging around an odor source is described that may indicate how wasps and other insects use their antennae and movement behavior to find odor sources of food, hosts, and mates when in close proximity.
DifFUZZY: A fuzzy spectral clustering algorithm for complex data sets
Ornella Cominetti,Anastasios Matzavinos,Sandhya Samarasinghe,Don Kulasiri,Philip K. Maini,Sijia Liu,Radek Erban +6 more
TL;DR: This method is better than traditional fuzzy clustering algorithms at handling data sets that are “curved”, elongated or those which contain clusters of different dispersion, including microarray and other high-throughput bioinformatics data.
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Computational modeling and experimental validation of odor detection behaviors of classically conditioned parasitic wasp, Microplitis croceipes
TL;DR: The overall results demonstrate the utility of mathematical models for interpreting experimental observations, gaining novel insights into the dynamic behavior of classically conditioned wasps, as well as broadening the practical uses of Wasp Hound.