Articles liés à Computational Biomathematics: Building and Simulating...
Synopsis
Reactive Publishing
Computational biomathematics sits at the intersection of biology, mathematics, and computer science. This book teaches you how to translate biological systems into working computational models and simulate them using code.
You will learn to:
- Build mathematical representations of biological processes (population dynamics, reaction networks, epidemiological models, ecological systems, and more)
- Implement models in Python from first principles
- Run deterministic and stochastic simulations
- Analyze, visualize, and validate simulation results
- Handle common challenges such as parameter estimation, sensitivity analysis, and model scaling
Each chapter combines clear mathematical derivation with practical, well-commented code examples that you can run, modify, and extend immediately. The focus is on understanding the modeling process rather than any single software package or black-box tool.
Whether you are a biologist seeking to add quantitative rigor, a mathematician or computer scientist exploring biological applications, or a student in computational biology, bioinformatics, or systems biology, this book provides a solid foundation for turning conceptual models into testable, simulatable code.
No prior experience in scientific computing is assumed beyond basic Python familiarity. All necessary numerical methods and biological context are introduced as needed.
Ideal for researchers, graduate students, and advanced undergraduates who want to move beyond theory and start building and experimenting with biological models in code.
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Computational Biomathematics: Building and Simulating Models with Code
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Computational Biomathematics
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Computational Biomathematics
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Computational Biomathematics (Paperback)
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Paperback. Etat : new. Paperback. Reactive PublishingComputational biomathematics sits at the intersection of biology, mathematics, and computer science. This book teaches you how to translate biological systems into working computational models and simulate them using code.You will learn to: Build mathematical representations of biological processes (population dynamics, reaction networks, epidemiological models, ecological systems, and more)Implement models in Python from first principlesRun deterministic and stochastic simulationsAnalyze, visualize, and validate simulation resultsHandle common challenges such as parameter estimation, sensitivity analysis, and model scalingEach chapter combines clear mathematical derivation with practical, well-commented code examples that you can run, modify, and extend immediately. The focus is on understanding the modeling process rather than any single software package or black-box tool.Whether you are a biologist seeking to add quantitative rigor, a mathematician or computer scientist exploring biological applications, or a student in computational biology, bioinformatics, or systems biology, this book provides a solid foundation for turning conceptual models into testable, simulatable code.No prior experience in scientific computing is assumed beyond basic Python familiarity. All necessary numerical methods and biological context are introduced as needed.Ideal for researchers, graduate students, and advanced undergraduates who want to move beyond theory and start building and experimenting with biological models in code. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798198108653
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Computational Biomathematics : Building and Simulating Models with Code
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Neuware - Reactive PublishingComputational biomathematics sits at the intersection of biology, mathematics, and computer science. This book teaches you how to translate biological systems into working computational models and simulate them using code.You will learn to: - Build mathematical representations of biological processes (population dynamics, reaction networks, epidemiological models, ecological systems, and more)- Implement models in Python from first principles- Run deterministic and stochastic simulations- Analyze, visualize, and validate simulation results- Handle common challenges such as parameter estimation, sensitivity analysis, and model scalingEach chapter combines clear mathematical derivation with practical, well-commented code examples that you can run, modify, and extend immediately. The focus is on understanding the modeling process rather than any single software package or black-box tool.Whether you are a biologist seeking to add quantitative rigor, a mathematician or computer scientist exploring biological applications, or a student in computational biology, bioinformatics, or systems biology, this book provides a solid foundation for turning conceptual models into testable, simulatable code.No prior experience in scientific computing is assumed beyond basic Python familiarity. All necessary numerical methods and biological context are introduced as needed.Ideal for researchers, graduate students, and advanced undergraduates who want to move beyond theory and start building and experimenting with biological models in code. N° de réf. du vendeur 9798198108653
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EUR 48
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Expédition depuis Allemagne vers Etats-Unis
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