M
Michael J. Chappell
Researcher at University of Warwick
Publications - 136
Citations - 2649
Michael J. Chappell is an academic researcher from University of Warwick. The author has contributed to research in topics: Identifiability & Nonlinear system. The author has an hindex of 26, co-authored 135 publications receiving 2442 citations.
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Journal ArticleDOI
Efficient Removal of Immunoglobulin Free Light Chains by Hemodialysis for Multiple Myeloma: In Vitro and In Vivo Studies
Colin A. Hutchison,Paul Cockwell,Steven D. Reid,Katie Chandler,Graham P. Mead,John Harrison,John Hattersley,Neil D. Evans,Michael J. Chappell,Mark Cook,Hermann Goehl,Markus Storr,Arthur R. Bradwell +12 more
TL;DR: Extended hemodialysis with the Gambro HCO 1100 dialyzer allowed continuous, safe removal of FLC in large amounts, and in vitro studies indicated that thisdialyzer was the most efficient of seven tested.
Journal ArticleDOI
Global identifiability of the parameters of nonlinear systems with specified inputs: a comparison of methods.
TL;DR: The two methods available for analyzing the global structural identifiability of the parameters of a nonlinear system with a specified input function, the Taylor series approach and the similarity transformation approach, are compared and contrasted through application to three examples.
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Evaluation of frequency and time-frequency spectral analysis of heart rate variability as a diagnostic marker of the sleep apnoea syndrome.
TL;DR: In non-REM sleep, spectral analysis of HRV appears to be a significantly better indicator of the SAHS than the current screening method of oximetry, and, in REM sleep, it is comparable withOximetry.
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Differential algebra methods for the study of the structural identifiability of rational function state-space models in the biosciences.
TL;DR: Methods from differential algebra are used to study the structural identifiability of biological and pharmacokinetics models expressed in state-space form and with a structure given by rational functions to obtain efficient algorithms.
Journal Article
Effect of dose, molecular size, affinity, and protein binding on tumor uptake of antibody or ligand: a biomathematical model.
GD Thomas,Michael J. Chappell,P.W. Dykes,David B. Ramsden,Keith R. Godfrey,John R. M. Ellis,Arthur R. Bradwell +6 more
TL;DR: A mathematical model has been developed to determine the best approach to improving tumor targeting with antibody and indicates that success requires an optimal combination of dose, size, and binding affinity of antibody.