메뉴 건너뛰기




Volumn 195, Issue , 2000, Pages 47-59

Identification of 72 phytoplankton species by radial basis function neural network analysis of flow cytometric data

Author keywords

Cryptomonads; Diatoms; Dinoflagellates; Flagellates; Neural networks; Principal component analysis; Prymnesiomonads; Radial basis functions

Indexed keywords

IDENTIFICATION METHOD;

EID: 0034737331     PISSN: 01718630     EISSN: None     Source Type: Journal    
DOI: 10.3354/meps195047     Document Type: Article
Times cited : (78)

References (33)
  • 2
    • 0001794519 scopus 로고    scopus 로고
    • Artificial neural networks for pattern recognition
    • Fielding AH (ed) Kluwer, Dordrecht
    • Boddy L, Morris CW (1999) Artificial neural networks for pattern recognition. In: Fielding AH (ed) Machine learning methods for ecological applications. Kluwer, Dordrecht, p 37-87
    • (1999) Machine Learning Methods for Ecological Applications , pp. 37-87
    • Boddy, L.1    Morris, C.W.2
  • 3
    • 0028203678 scopus 로고
    • Neural network analysis of flow cytometric data for 40 marine phytoplankton species
    • Boddy L, Morris CW, Wilkins MF, Tarran GA, Burkill PH (1994) Neural network analysis of flow cytometric data for 40 marine phytoplankton species. Cytometry 15:283-293
    • (1994) Cytometry , vol.15 , pp. 283-293
    • Boddy, L.1    Morris, C.W.2    Wilkins, M.F.3    Tarran, G.A.4    Burkill, P.H.5
  • 4
    • 0032292088 scopus 로고    scopus 로고
    • Effects of missing data on neural network identification of biological taxa: RBF network discrimination of phytoplankton from flow cytometry data
    • Dagli H, Akay M, Buczak CLP, Ersoy AL, Fernandez BR (eds) American Society of Mechanical Engineers Press, New York
    • Boddy L, Wilkins MF, Morris CW (1998) Effects of missing data on neural network identification of biological taxa: RBF network discrimination of phytoplankton from flow cytometry data. In: Dagli H, Akay M, Buczak CLP, Ersoy AL, Fernandez BR (eds) Intelligent engineering systems through artificial neural networks, Vol 8. American Society of Mechanical Engineers Press, New York, p 655-666
    • (1998) Intelligent Engineering Systems Through Artificial Neural Networks , vol.8 , pp. 655-666
    • Boddy, L.1    Wilkins, M.F.2    Morris, C.W.3
  • 5
    • 0001828322 scopus 로고
    • The rapid analysis of single marine cells by flow cytometry
    • Burkill PH, Mantoura RFC (1990) The rapid analysis of single marine cells by flow cytometry. Philos Trans R Soc A 333: 99-112
    • (1990) Philos Trans R Soc A , vol.333 , pp. 99-112
    • Burkill, P.H.1    Mantoura, R.F.C.2
  • 6
    • 0029669499 scopus 로고    scopus 로고
    • Discrimination of marine phytoplankton species through the statistical analysis of their flow cytometric signatures
    • Carr MR, Tarran GA, Burkill PH (1996) Discrimination of marine phytoplankton species through the statistical analysis of their flow cytometric signatures. J Plankton Res 18: 1225-1238
    • (1996) J Plankton Res , vol.18 , pp. 1225-1238
    • Carr, M.R.1    Tarran, G.A.2    Burkill, P.H.3
  • 8
    • 0026116468 scopus 로고
    • Orthogonal least squares learning algorithm for radial basis function networks
    • Chen S, Cowan CFN, Grant PM (1991) Orthogonal least squares learning algorithm for radial basis function networks. IEEE Trans Neural Networks 2:302-309
    • (1991) IEEE Trans Neural Networks , vol.2 , pp. 302-309
    • Chen, S.1    Cowan, C.F.N.2    Grant, P.M.3
  • 10
    • 0026603242 scopus 로고
    • Analysing multivariate flow cytometric data in aquatic sciences
    • Demers S, Kim J, Legendre P, Legendre L (1992) Analysing multivariate flow cytometric data in aquatic sciences. Cytometry 13:291-298
    • (1992) Cytometry , vol.13 , pp. 291-298
    • Demers, S.1    Kim, J.2    Legendre, P.3    Legendre, L.4
  • 12
    • 0024723987 scopus 로고
    • Use of a neural net computer system for analysis of flow cytometric data of phytoplankton populations
    • Frankel DS, Olson RJ, Frankel SL, Chisholm SW (1989) Use of a neural net computer system for analysis of flow cytometric data of phytoplankton populations. Cytometry 10: 540-550
    • (1989) Cytometry , vol.10 , pp. 540-550
    • Frankel, D.S.1    Olson, R.J.2    Frankel, S.L.3    Chisholm, S.W.4
  • 13
    • 0029873409 scopus 로고    scopus 로고
    • Application of neural networks to flow cytometry data analysis and real-time cell classification
    • Frankel DS, Frankel SL, Binder BJ, Vogt RF (1996) Application of neural networks to flow cytometry data analysis and real-time cell classification. Cytometry 23:290-302
    • (1996) Cytometry , vol.23 , pp. 290-302
    • Frankel, D.S.1    Frankel, S.L.2    Binder, B.J.3    Vogt, R.F.4
  • 15
    • 73049174685 scopus 로고
    • Studies on marine planktonic diatoms. I. Cyclotella nana (Hustedt) and Detonula confervacae (Cleve) Gran
    • Guillard RRL, Ryther JH (1962) Studies on marine planktonic diatoms. I. Cyclotella nana (Hustedt) and Detonula confervacae (Cleve) Gran. Can J Microbiol 8:229-239
    • (1962) Can J Microbiol , vol.8 , pp. 229-239
    • Guillard, R.R.L.1    Ryther, J.H.2
  • 18
    • 85032752004 scopus 로고
    • Progress in supervised neural networks - What's new since Lippmann?
    • Hush DR, Horne BG (1993) Progress in supervised neural networks - what's new since Lippmann? IEEE Sig Proc Mag 10:8-39
    • (1993) IEEE Sig Proc Mag , vol.10 , pp. 8-39
    • Hush, D.R.1    Horne, B.G.2
  • 21
    • 0025489075 scopus 로고
    • The self-organising map
    • Kohonen T (1990) The self-organising map. Proc IEEE 78: 1464-1480
    • (1990) Proc IEEE , vol.78 , pp. 1464-1480
    • Kohonen, T.1
  • 22
    • 0031880802 scopus 로고    scopus 로고
    • Identification of species in the genus Pestalotiopsis from spore morphometric data: A comparison of some neural and non-neural methods
    • Morgan A, Boddy L, Morris CW, Mordue JEM (1998) Identification of species in the genus Pestalotiopsis from spore morphometric data: a comparison of some neural and non-neural methods. Mycol Res 102:975-984
    • (1998) Mycol Res , vol.102 , pp. 975-984
    • Morgan, A.1    Boddy, L.2    Morris, C.W.3    Mordue, J.E.M.4
  • 23
    • 0030308704 scopus 로고    scopus 로고
    • Classification as unknown by RBF networks: Discriminating phytoplankton taxa from flow cytometry data
    • Dagli CH, Akay M, Chen CLP, Fernandez BR, Ghosh J (eds) American Society of Mechanical Engineers Press, New York
    • Morris CW, Boddy L (1996) Classification as unknown by RBF networks: discriminating phytoplankton taxa from flow cytometry data. In: Dagli CH, Akay M, Chen CLP, Fernandez BR, Ghosh J (eds) Intelligent engineering systems through artificial neural networks, Vol 6. American Society of Mechanical Engineers Press, New York, p 629-634
    • (1996) Intelligent Engineering Systems Through Artificial Neural Networks , vol.6 , pp. 629-634
    • Morris, C.W.1    Boddy, L.2
  • 24
    • 84990556022 scopus 로고
    • Identification of basidiomycete spores by neural network analysis of flow cytometry data
    • Morris CW, Boddy L, Allman R (1992) Identification of basidiomycete spores by neural network analysis of flow cytometry data. Mycol Res 96:697-701
    • (1992) Mycol Res , vol.96 , pp. 697-701
    • Morris, C.W.1    Boddy, L.2    Allman, R.3
  • 25
    • 0001595997 scopus 로고
    • Neural network classifiers estimate Bayesian a posteriori probabilities
    • Richard MD, Lippmann RP (1991) Neural network classifiers estimate Bayesian a posteriori probabilities. Neural Comp 3:461-483
    • (1991) Neural Comp , vol.3 , pp. 461-483
    • Richard, M.D.1    Lippmann, R.P.2
  • 29
    • 0000517353 scopus 로고
    • Improving the performance of radial basis function networks by learning center locations
    • Wettschereck D, Dietterich T (1992) Improving the performance of radial basis function networks by learning center locations. Adv Neural Info Process Syst 4:1133-1140
    • (1992) Adv Neural Info Process Syst , vol.4 , pp. 1133-1140
    • Wettschereck, D.1    Dietterich, T.2
  • 30
    • 0029919556 scopus 로고    scopus 로고
    • A comparison of some neural and non-neural methods for identification of phytoplankton from flow cytometry data
    • Wilkins MF, Boddy L, Morris CW, Jonker R (1996) A comparison of some neural and non-neural methods for identification of phytoplankton from flow cytometry data. CABIOS 12:9-18
    • (1996) CABIOS , vol.12 , pp. 9-18
    • Wilkins, M.F.1    Boddy, L.2    Morris, C.W.3    Jonker, R.4
  • 31
    • 0002663117 scopus 로고
    • Kohonen maps and learning vector quantization neural networks for analysis of multivariate biological data
    • Wilkins MF, Boddy L, Morris CW (1994a) Kohonen maps and learning vector quantization neural networks for analysis of multivariate biological data. Binary 6:64-72
    • (1994) Binary , vol.6 , pp. 64-72
    • Wilkins, M.F.1    Boddy, L.2    Morris, C.W.3
  • 32
    • 0028362299 scopus 로고
    • A comparison of radial basis function and backpropagation neural networks for identification of marine phytoplankton from multivariate flow cytometry data
    • Wilkins MF, Morris CW, Boddy L (1994b) A comparison of radial basis function and backpropagation neural networks for identification of marine phytoplankton from multivariate flow cytometry data. CABIOS 10:285-294
    • (1994) CABIOS , vol.10 , pp. 285-294
    • Wilkins, M.F.1    Morris, C.W.2    Boddy, L.3
  • 33
    • 0032832628 scopus 로고    scopus 로고
    • Identification of phytoplankton from flow cytometry data using radial basis function neural networks
    • Wilkins MF, Boddy L, Morris CW, Jonker R (1999) Identification of phytoplankton from flow cytometry data using radial basis function neural networks. Appl Environ Microbiol 65:4404-4410
    • (1999) Appl Environ Microbiol , vol.65 , pp. 4404-4410
    • Wilkins, M.F.1    Boddy, L.2    Morris, C.W.3    Jonker, R.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.