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Mathematical Modelling and Computers in Endocrinology

  • Book
  • © 1980

Overview

Authors:
  1. James E. A. McIntosh

    1. Department of Obstetrics and Gynaecology, University of Adelaide, Adelaide, Australia

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  2. Rosalind P. McIntosh

    1. Lucy Cavendish College, Cambridge, UK

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    You can also search for this author in PubMed   Google Scholar

Part of the book series: Monographs on Endocrinology (ENDOCRINOLOGY, volume 16)

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Table of contents (12 chapters)

  1. Front Matter

    Pages I-XII
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  2. Modelling in Biology

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 1-25

  3. Mathematical Descriptions of Biological Models

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 26-73

  4. Comparing Models with Experimental Results

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 74-102

  5. Design of Analytical Experiments

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 103-114

  6. Dynamic Systems: Clearance and Compartmental Analysis

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 115-142

  7. Ligand-Protein Interaction and Competitive Displacement Assays

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 143-170

  8. Mathematical Modelling of Biological Rhythms

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 171-200

  9. Large Systems: Modelling Ovulatory Cycles

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 201-225

  10. Stochastic Models

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 226-241

  11. Appendix A: A Summary of Relevant Statistics

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 242-249

  12. Appendix B: Computer Programs

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 250-293

  13. Appendix C: Analytical Integration by Laplace Transform

    • James E. A. McIntosh, Rosalind P. McIntosh
    Pages 294-295

  14. Back Matter

    Pages 296-340
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Keywords

About this book

The building of conceptual models is an inherent part of our interaction with the world, and the foundation of scientific investigation. Scientists often perform the processes of modelling subconsciously, unaware of the scope and significance of this activity, and the techniques available to assist in the description and testing of their ideas. Mathematics has three important contributions to make in biological modelling: (1) it provides unambiguous languages for expressing relationships at both qualitative and quantitative levels of observation; (2) it allows effective analysis and prediction of model behaviour, and can thereby organize experimental effort productively; (3) it offers rigorous methods of testing hypotheses by comparing models with experimental data; by providing a means of objectively excluding unsuitable concepts, the development of ideas is given a sound experimental basis. Many modern mathematical techniques can be exploited only with the aid of computers. These machines not only provide increased speed and accuracy in determining the consequences of model assumptions, but also greatly extend the range of problems which can be explored. The impact of computers in the biological sciences has been widespread and revolutionary, and will continue to be so.

Authors and Affiliations

  • Department of Obstetrics and Gynaecology, University of Adelaide, Adelaide, Australia

    James E. A. McIntosh

  • Lucy Cavendish College, Cambridge, UK

    Rosalind P. McIntosh

Bibliographic Information

  • Book Title: Mathematical Modelling and Computers in Endocrinology

  • Authors: James E. A. McIntosh, Rosalind P. McIntosh

  • Series Title: Monographs on Endocrinology

  • DOI: https://doi.org/10.1007/978-3-642-81401-3

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin, Heidelberg 1980

  • Softcover ISBN: 978-3-642-81403-7Published: 16 December 2011

  • eBook ISBN: 978-3-642-81401-3Published: 06 December 2012

  • Series ISSN: 0077-1015

  • Edition Number: 1

  • Number of Pages: XII, 340

  • Topics: Endocrinology, Mathematical and Computational Biology

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