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Discrete-Time Model Representations for Biochemical Pathways

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Trends in Intelligent Systems and Computer Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 6))

Based on much experimentation, traditional biochemists and molecular biologists have developed many qualitative models and hypotheses for biochemical pathway study [7, 26, 28]. However, in order to evaluate the completeness and usefulness of a hypothesis, produce predictions for further testing, and better understand the interaction and dynamic of pathway components, qualitative models are no longer adequate. There has recently been a focus on a more quantitative approach in systems biology study. In the past decade, numerous approaches for quantitative modeling of biochemical pathway dynamics have been proposed (e.g., [1, 4, 15, 29, 30, 34, 36], among others).

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Authors and Affiliations

  1. School of Electronic and Electrical Engineering, The University of Manchester, Manchester, M60 1QD, UK

    Fei He & Martin Brown

  2. Department of Electronic Engineering, City University of Hong Kong, Hong Kong

    Fei He & Lam Fat Yeung

Authors
  1. Fei He
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  2. Lam Fat Yeung
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  3. Martin Brown
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Tijuana Institute of Technology, 4207, Chula Vista, CA, 91909, USA

    Oscar Castillo

  2. Department of Systems Science and Engineering Yu-Quan Campus, Zhejiang University College of Electrical Engineering, 310027, Hangzhou, People's Republic of China

    Li Xu

  3. IAENG Secretariat, 37–39 Hung To Road Unit 1, 1/F, Hong Kong, People's Republic of China

    Sio-Iong Ao

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He, F., Yeung, L.F., Brown, M. (2008). Discrete-Time Model Representations for Biochemical Pathways. In: Castillo, O., Xu, L., Ao, SI. (eds) Trends in Intelligent Systems and Computer Engineering. Lecture Notes in Electrical Engineering, vol 6. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-74935-8_19

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  • DOI: https://doi.org/10.1007/978-0-387-74935-8_19

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-74934-1

  • Online ISBN: 978-0-387-74935-8

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