Elsevier Quantitative Biology: Mathematical Modeling and Computation

Quantitative Biology provides quantitative and data-driven approaches for analyzing biological and bio-inspired systems, covering the foundations of mathematical modeling, analysis, and computation. The book presents a practical mix of both theory and computation for a variety of biological applications, with tied-in, engaging project activities, instruction, programming language, and technological tools. Modeling approaches combine mathematical foundations, statistical reasoning, and computational thinking, with applications in compartmental, agent-based, bio image, biological interaction, and neural network modeling, as well as machine learning, parameter identification, and applications across societal challenges. Each chapter includes exposure to models and modeling, a foundational instructional framework, benchmark applications, and numerical simulations with a literate programming guided style that helps readers go beyond replication models and into prediction and data-driven discovery. A companion website also features interactive code to accompany projects across each chapter. Introduces and demonstrates mathematical modeling, analysis, and computation for biological and bio-inspired systems Presents and instructs in computation for a variety of biological applications via engaging project activities, benchmark examples, and technology tools Offers insights into replicative models for biological systems, empowering prediction and data-driven discovery Includes a foundational instructional framework, benchmark applications, and numerical simulations with a literate programming guided style across all chapters Features a companion webpage with interactive code to accompany chapter projects