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L Boddy

Showing results (11-20 of 34) with videos related to

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Computer 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.
Microbial Ecology|March 3, 2004
An evaluation of 18S rDNA approaches for the study of fungal diversity in grassland soilsJ Hunt, L Boddy, P F Randerson, 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|June 29, 2001
Comparison of five clustering algorithms to classify phytoplankton from flow cytometry dataM F Wilkins, S A Hardy, L Boddy, et al.
Science (New York, N.Y.)|April 7, 2007
Rapid and recent changes in fungal fruiting patternsA C Gange, E G Gange, T H Sparks, et al.
BJU International|March 31, 2004
Intra-individual variation of serum prostate specific antigen levels in men with benign prostate biopsiesJ L Boddy, S Dev, D J Pike, et al.
ISME Communications|November 8, 2023
Network traits predict ecological strategies in fungiC A Aguilar-Trigueros, L Boddy, M C Rillig, et al.
Applied and Environmental Microbiology|November 5, 2017
Interdependence of Primary Metabolism and Xenobiotic Mitigation Characterizes the Proteome of Bjerkandera adusta during Wood DecompositionS C Moody, E Dudley, J Hiscox, 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.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|March 5, 2005
Prospective study of quantitation of plasma DNA levels in the diagnosis of malignant versus benign prostate diseaseJane L Boddy, Shira Gal, Peter R Malone, et al.
Pageof 4

Showing results (11-20 of 34) with videos related to

Sort By:
Pageof 4
Computer 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.
Microbial Ecology|March 3, 2004
An evaluation of 18S rDNA approaches for the study of fungal diversity in grassland soilsJ Hunt, L Boddy, P F Randerson, 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|June 29, 2001
Comparison of five clustering algorithms to classify phytoplankton from flow cytometry dataM F Wilkins, S A Hardy, L Boddy, et al.
Science (New York, N.Y.)|April 7, 2007
Rapid and recent changes in fungal fruiting patternsA C Gange, E G Gange, T H Sparks, et al.
BJU International|March 31, 2004
Intra-individual variation of serum prostate specific antigen levels in men with benign prostate biopsiesJ L Boddy, S Dev, D J Pike, et al.
ISME Communications|November 8, 2023
Network traits predict ecological strategies in fungiC A Aguilar-Trigueros, L Boddy, M C Rillig, et al.
Applied and Environmental Microbiology|November 5, 2017
Interdependence of Primary Metabolism and Xenobiotic Mitigation Characterizes the Proteome of Bjerkandera adusta during Wood DecompositionS C Moody, E Dudley, J Hiscox, 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.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|March 5, 2005
Prospective study of quantitation of plasma DNA levels in the diagnosis of malignant versus benign prostate diseaseJane L Boddy, Shira Gal, Peter R Malone, et al.
Pageof 4