Computational Cell Biology

  • Christopher P. Fall
  • Eric S. Marland
  • John M. Wagner
  • John J. Tyson

Part of the Interdisciplinary Applied Mathematics book series (IAM, volume 20)

Table of contents

  1. Front Matter
    Pages I-XX
  2. Introductory Course

    1. Front Matter
      Pages 1-1
    2. Christopher P. Fall, Joel E. Keizer
      Pages 3-20
    3. Christopher P. Fall, Joel E. Keizer
      Pages 21-52
    4. Eric S. Marland, Joel E. Keizer
      Pages 53-76
    5. James P. Keener, Joel E. Keizer
      Pages 77-100
    6. Arthur S. Sherman, Yue-Xian Li, Joel E. Keizer
      Pages 101-139
    7. John Rinzel
      Pages 140-169
  3. Advanced Material

    1. Front Matter
      Pages 169-169
    2. James P. Keener
      Pages 171-197
    3. Gregory D. Smith, John E. Pearson, Joel E. Keizer
      Pages 198-229
    4. John J. Tyson
      Pages 230-260
    5. John J. Tyson, Béla Novák
      Pages 261-284
    6. Gregory D. Smith
      Pages 285-319
    7. Alex Mogilner, Timothy C. Elston, Hongyun Wang, George Oster
      Pages 320-353
    8. Alex Mogilner, Timothy C. Elston, Hongyun Wang, George Oster
      Pages 354-377
  4. Back Matter
    Pages 378-468

About this book

Introduction

 

This textbook provides an introduction to dynamic modeling in cell biology, emphasizing computational approaches based on realistic molecular mechanisms. It is designed to introduce cell biology and neuroscience students to computational modeling, and applied mathematics students, theoretical biologists, and engineers to many of the problems in dynamical cell biology. This volume was conceived of and begun by Professor Joel Keizer based on his many years of teaching and research together with his colleagues. The project was expanded and finished by his students and friends after his untimely death in 1999.

Carefully selected examples are used to motivate the concepts and techniques of computational cell biology, through a progression of increasingly more complex and demanding cases. Illustrative exercises are included with every chapter, and mathematical and computational appendices are provided for reference. This textbook will be useful for advanced undergraduate and graduate theoretical biologists, and for mathematic students and life scientists who wish to learn about modeling in cell biology.

"What better tribute to the late Joel Keizer than to expand his unfinished accounts of teaching and research to a splendid book. Computational Cell Biology performs much more than it promises, for it also deals with considerable analytical material and with aspects of molecular biology. There's something for everybody interested in how modeling leads to greater understanding in the core of the biological sciences."

-Lee Segel (Weizmann Institute)

Keywords

algorithms cell biology computational cell biology dynamical cell biology mathematical biology modeling in cell biology molecular biology molecular mechanisms

Editors and affiliations

  • Christopher P. Fall
    • 1
  • Eric S. Marland
    • 2
  • John M. Wagner
    • 3
  • John J. Tyson
    • 4
  1. 1.Center for Neural ScienceNew York UniversityUSA
  2. 2.Department of Mathematical SciencesAppalachian State UniversityBooneUSA
  3. 3.Center for Biomedical Imaging TechnologyUniversity of Connecticut Health CenterFarmingtonUSA
  4. 4.Department of BiologyVirginia Polytechnic InstituteBlacksburgUSA

Bibliographic information

  • DOI https://doi.org/10.1007/b97701
  • Copyright Information Springer-Verlag New York, Inc. 2002
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-95369-4
  • Online ISBN 978-0-387-22459-6
  • Series Print ISSN 0939-6047
  • About this book