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  • GTP  (1)
  • Robust statistics  (1)
  • artificial neural network  (1)
  • 1990-1994  (3)
  • 1
    Electronic Resource
    Electronic Resource
    Artificial neural networks applied to potentiometric titration of multi-component polybasic acid mixtures (1993)
    Springer
    Microchimica acta 111 (1993), S. 199-206 
    Details
    ISSN: 1436-5073
    Keywords: chemometrics ; artificial neural network ; multi-component calibration ; potentiometric acid-base titration
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Abstract A three-layer artificial neural network model with back-propagation of error is used to treat potentiometric acid-base titration data for estimating the concentrations of individual components in polybasic weak acid mixtures. The network's architecture and parameters were optimized and an empirical rule for dynamically adjusting the learning rate is put forward to improve the network's performance. Satisfactory prediction results were obtained for three-component samples containing maleic acid, propandioic acid and succinic acid with an average relative error of 4.5%.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01245307
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  • 2
    Electronic Resource
    Electronic Resource
    Molecular cloning and biochemical characterization of a receptor-like serine/threonine kinase from rice (1994)
    Springer
    Plant molecular biology 26 (1994), S. 791-803 
    Details
    ISSN: 1573-5028
    Keywords: ATP ; GTP ; protein kinase ; receptor ; rice ; signal transduction
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract A receptor-like protein kinase, OsPK10, has been cloned from rice (Oryza sativa). The 2.8 kb cDNA contains an open reading frame capable of encoding a peptide sequence of 824 amino acids. The topological features of the predicted OsPK10 protein include an N-terminal signal peptide, a cysteine-rich extracellular ligand-binding domain, a membrane-spanning segment, and a cytoplasmic domain possessing all the hallmarks of catalytic domains of eukaryotic protein kinases. The cytoplasmic domain was selectively expressed in Escherichia coli and assayed for kinase activity. The results show the protein is capable of autophosphorylation using either ATP or GTP as the phosphate donor. Phosphoamino acid analysis reveals phosphorylation of threonines, consistent with the substrate specificity indicated by sequence motifs in the catalytic core. A single amino acid substitution of Glu for Lys-528 completely abolishes autophosphorylation activity. DNA gel blot analyses suggest that the haploid rice genome contains a single copy of the OsPK10 gene. OsPK10 transcripts appear to be more abundant in shoots than in roots of rice seedlings.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00028849
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  • 3
    Electronic Resource
    Electronic Resource
    Robust principal component analysis by projection pursuit (1993)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 7 (1993), S. 527-541 
    Details
    ISSN: 0886-9383
    Keywords: Principal component analysis ; Projection pursuit ; Simulated annealing algorithm ; Robust statistics ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Principal component analysis (PCA) is a widely used technique in chemometrics. The classical PCA method is, unfortunately, non-robust, since the variance is adopted as the objective function. In this paper, projection pursuit (PP) is used to carry out PCA with a criterion which is more robust than the variance. In addition, the generalized simulated annealing (GSA) algorithm is introduced as an optimization procedure in the process of PP calculation to guarantee the global optimum. The results for simulated data sets show that PCA via PP is resistant to the deviation of the error distribution from the normal one. The method is especially recommended for use in cases with possible outlier(s) existing in the data.
    Additional Material: 7 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180070606
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