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Cytometry|June 29, 2001
Comparison of five clustering algorithms to classify phytoplankton from flow cytometry dataM F Wilkins, S A Hardy, L Boddy, et al.Journal of Microbiological Methods|November 21, 2000
Proportion estimation with confidence limitsM F Wilkins, L Boddy, C W MorrisComputer Applications in the Biosciences : CABIOS|June 1, 1994
A comparison of Radial Basis Function and backpropagation neural networks for identification of marine phytoplankton from multivariate flow cytometry dataM F Wilkins, C W Morris, L BoddyComputer Applications in the Biosciences : CABIOS|February 1, 1996
A comparison of some neural and non-neural methods for identification of phytoplankton from flow cytometry dataM F Wilkins, L Boddy, C W Morris, et al.Applied and Environmental Microbiology|October 3, 1999
Identification of phytoplankton from flow cytometry data by using radial basis function neural networksM F Wilkins, L Boddy, C W Morris, et al.Cytometry|April 1, 1994
Neural network analysis of flow cytometric data for 40 marine phytoplankton speciesL Boddy, C W Morris, M F Wilkins, et al.Journal of Microbiological Methods|November 21, 2000
Training radial basis function neural networks: effects of training set size and imbalanced training setsL Al-Haddad, C W Morris, L BoddyMicrobial Ecology|July 9, 2005
Inhibition and stimulation effects in communities of wood decay fungi: exudates from colonized wood influence growth by other speciesJ Heilmann-Clausen, L BoddyStudies in Mycology|June 19, 2018
Fungus wars: basidiomycete battles in wood decayJ Hiscox, J O'Leary, L BoddyPageof 5