Mathematical Concepts and Methods in Modern Biology

Using Modern Discrete Models

Nonfiction, Science & Nature, Mathematics, Applied, Science
Cover of the book Mathematical Concepts and Methods in Modern Biology by , Elsevier Science
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Author: ISBN: 9780124157934
Publisher: Elsevier Science Publication: February 26, 2013
Imprint: Academic Press Language: English
Author:
ISBN: 9780124157934
Publisher: Elsevier Science
Publication: February 26, 2013
Imprint: Academic Press
Language: English

Mathematical Concepts and Methods in Modern Biology offers a quantitative framework for analyzing, predicting, and modulating the behavior of complex biological systems. The book presents important mathematical concepts, methods and tools in the context of essential questions raised in modern biology.

Designed around the principles of project-based learning and problem-solving, the book considers biological topics such as neuronal networks, plant population growth, metabolic pathways, and phylogenetic tree reconstruction. The mathematical modeling tools brought to bear on these topics include Boolean and ordinary differential equations, projection matrices, agent-based modeling and several algebraic approaches. Heavy computation in some of the examples is eased by the use of freely available open-source software.

  • Features self-contained chapters with real biological research examples using freely available computational tools
  • Spans several mathematical techniques at basic to advanced levelsĀ 
  • Offers broad perspective on the uses of algebraic geometry/polynomial algebra in molecular systems biology
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Mathematical Concepts and Methods in Modern Biology offers a quantitative framework for analyzing, predicting, and modulating the behavior of complex biological systems. The book presents important mathematical concepts, methods and tools in the context of essential questions raised in modern biology.

Designed around the principles of project-based learning and problem-solving, the book considers biological topics such as neuronal networks, plant population growth, metabolic pathways, and phylogenetic tree reconstruction. The mathematical modeling tools brought to bear on these topics include Boolean and ordinary differential equations, projection matrices, agent-based modeling and several algebraic approaches. Heavy computation in some of the examples is eased by the use of freely available open-source software.

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