Modeling Biological Systems:: Principles and Applications by James W. Haefner PDF

By James W. Haefner

ISBN-10: 0387250115

ISBN-13: 9780387250113

ISBN-10: 0387250123

ISBN-13: 9780387250120

This can be the second one version of a textbook presently released by means of Springer for a direction in mathematical modeling and laptop simulation for biologists on the complicated undergraduate and introductory graduate point. The viewers for this variation is identical to that of the former one: complex point classes in computational biology, in addition to researchers retooling themselves. This new version contains a CD-ROM with actual examples of versions as educating instruments.

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Example text

Thus, the two extreme models, random and omniscient, bound the range of possible explanations. The base model concept is similar to a null or neutral model (Caswell 1976a): models that exclude biological mechanisms pertinent to a particular hypothesis. The value of including these models is that they are simple explanations. " Or, to put it another way, simple models are good, but getting the right answer for the right reason is also good. Chapter 8 presents methods for choosing the better of alternative models.

There are several key points in this objective that deserve elaboration. First, the term total-system model refers to the inclusion of abiotic, producer, consumer, decomposer, and nutrient subsystems. This requirement was imposed to assure that the modeling effort played the integrative role delegated to it ... Second, biomass dynamics identifies our principal concern with carbon or energy flow through the system. Focus on biomass facilitated the comparison of model and data but turned out to be unfortunate because it is not conserved.

The dynamics of many biological processes depend on several interacting variables. There are two broad applications of this concept in modeling: (1) the variables are at the same level of biological organization but may interact in their influence on the dynamics, or (2) the variables are at different levels of organization, but both are needed to address the model objectives. l h o variables (A and B) are on the same level of biological organization if all of the measurements that can logically be made on A can also be made on B, and there are no measurements that can be made on B that cannot be made on A.

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Modeling Biological Systems:: Principles and Applications by James W. Haefner


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