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System Modeling in Cellular Biology: From Concepts to Nuts and Bolts [Hardcover]

by Zoltan Szallasi, Jörg Stelling, Vipul Periwal
3.7 out of 5 stars  See all reviews (3 customer reviews)

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Book Description

March 24, 2006 0262195488 978-0262195485 1

Research in systems biology requires the collaboration of researchers from diverse backgrounds, including biology, computer science, mathematics, statistics, physics, and biochemistry. These collaborations, necessary because of the enormous breadth of background needed for research in this field, can be hindered by differing understandings of the limitations and applicability of techniques and concerns from different disciplines. This comprehensive introduction and overview of system modeling in biology makes the relevant background material from all pertinent fields accessible to researchers with different backgrounds.The emerging area of systems level modeling in cellular biology has lacked a critical and thorough overview. This book fills that gap. It is the first to provide the necessary critical comparison of concepts and approaches, with an emphasis on their possible applications. It presents key concepts and their theoretical background, including the concepts of robustness and modularity and their exploitation to study biological systems; the best-known modeling approaches, and their advantages and disadvantages; lessons from the application of mathematical models to the study of cellular biology; and available modeling tools and datasets, along with their computational limitations.



Editorial Reviews

Review

"Whether for graduate students or researchers, this book provides an excellent introduction to systems biology modeling." Steven S. Andrews Quarterly Review of Biology

About the Author

Zoltan Szallasi is Professor at the Center for Biological Sequence Analysis, Technical University of Denmark.

Jörg Stelling is a faculty member of the Department of Biosystems Science and Engineering at ETH Zürich.

Vipul Periwal is with the Mathematical Cell ModelingSection, NIDDK, National Institute of Health.

Product Details

  • Hardcover: 464 pages
  • Publisher: The MIT Press; 1 edition (March 24, 2006)
  • Language: English
  • ISBN-10: 0262195488
  • ISBN-13: 978-0262195485
  • Product Dimensions: 9.3 x 7.2 x 1.1 inches
  • Shipping Weight: 2 pounds (View shipping rates and policies)
  • Average Customer Review: 3.7 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #1,564,307 in Books (See Top 100 in Books)

Customer Reviews

3.7 out of 5 stars
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3.7 out of 5 stars
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Most Helpful Customer Reviews
11 of 11 people found the following review helpful
Format:Hardcover|Verified Purchase
I'm torn between giving this book 3 or 4 stars. On one hand, it is enjoyable to read and a great value for Amazon's discounted price. On the other hand, the book tries to tackle many modeling techniques at once; I often found myself wishing for more complete descriptions than were provided.

The first section introduces basic concepts of mathematical modeling and considers structures and behaviors characteristic of biological models: The text opens with a discussion of the compromise between model scope and informativeness. Trade-offs of biological robustness and complexity are discussed. Modularity is explored as a unifying property of biological systems.

The next section discusses a range of mathematical modeling frameworks. Bayesian logic is introduced as a means to discriminate among competing models (hypotheses) of biological systems. Quasi-steady state stoichiometric methods, non-linear ODEs, PDEs, and stochastic methods are each given a chapter. Biological network topology is also discussed. While the topics are presented well (some better than others), many (especially the topology and PDE chapters) would benefit from more extensive coverage and mathematical background. The toy model examples are also very simplistic; I would have liked to see discussion of special considerations for higher-dimensional systems.

The third section was the most useful for me and at the same time the most frustrating. It discusses practical issues: experimental data collection, model identification, parameter estimation, and control theory. There is a chapter on gene regulatory systems (think BioBricks or Uri Alon's work) and a brief discussion of multi-scale (cellular/tissue/organ) models.
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1 of 3 people found the following review helpful
4.0 out of 5 stars Pretty good text October 5, 2009
By D-Stan
Format:Hardcover|Verified Purchase
This text has been very helpful in understanding the theory behind systems biology. Although it's a pretty good text, some of the chapters are not very readable. I'm sure that's in part due to the fact that sys bio is new to me, but it's also due to some unclear writing. Nevertheless, I still recommend it for computer scientists and biologists that would like a better understanding of mathematical modeling of biological systems.
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0 of 5 people found the following review helpful
4.0 out of 5 stars good book! December 30, 2007
By Yi Fan
Format:Hardcover
A nicely written book for beginner-to-intermediate level system biologists.
The math models are neat and helpful, and the price is certainly good enough for its value.
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Systems Biology Books
Of the books you mentioned, I've read Alon, Wilkinson, and Szallasi. Each has different strengths and weaknesses and their usefulness will probably depend on your background.

Alon's book is a great read. It's what I'd consider a programmer's or physicist's introduction to systems biology. ... Read more
Aug 12, 2009 by J. Hengenius |  See all 2 posts
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