Literature DB >> 8899971

Quantitative analysis of multivariate data using artificial neural networks: a tutorial review and applications to the deconvolution of pyrolysis mass spectra.

R Goodacre1, M J Neal, D B Kell.   

Abstract

The implementation of artificial neural networks (ANNs) to the analysis of multivariate data is reviewed, with particular reference to the analysis of pyrolysis mass spectra. The need for and benefits of multivariate data analysis are explained followed by a discussion of ANNs and their optimisation. Finally, an example of the use of ANNs for the quantitative deconvolution of the pyrolysis mass spectra of Staphylococcus aureus mixed with Escherichia coli is demonstrated.

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Year:  1996        PMID: 8899971     DOI: 10.1016/s0934-8840(96)80004-1

Source DB:  PubMed          Journal:  Zentralbl Bakteriol        ISSN: 0934-8840


  6 in total

1.  Rapid authentication of animal cell lines using pyrolysis mass spectrometry and auto-associative artificial neural networks.

Authors:  R Goodacre; D J Rischert; P M Evans; D B Kell
Journal:  Cytotechnology       Date:  1996-01       Impact factor: 2.058

Review 2.  Flow cytometry and cell sorting of heterogeneous microbial populations: the importance of single-cell analyses.

Authors:  H M Davey; D B Kell
Journal:  Microbiol Rev       Date:  1996-12

3.  Advanced Multidimensional Separations in Mass Spectrometry: Navigating the Big Data Deluge.

Authors:  Jody C May; John A McLean
Journal:  Annu Rev Anal Chem (Palo Alto Calif)       Date:  2016-03-30       Impact factor: 10.745

4.  Structural reliability calculation method based on the dual neural network and direct integration method.

Authors:  Haibin Li; Yun He; Xiaobo Nie
Journal:  Neural Comput Appl       Date:  2016-08-23       Impact factor: 5.606

5.  Soft Computing of a Medically Important Arthropod Vector with Autoregressive Recurrent and Focused Time Delay Artificial Neural Networks.

Authors:  Petros Damos; José Tuells; Pablo Caballero
Journal:  Insects       Date:  2021-05-31       Impact factor: 2.769

6.  Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks.

Authors:  Elisa Valletta; Lukáš Kučera; Lubomír Prokeš; Filippo Amato; Tiziana Pivetta; Aleš Hampl; Josef Havel; Petr Vaňhara
Journal:  PLoS One       Date:  2016-01-28       Impact factor: 3.240

  6 in total

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