Joshua S. Weitz is professor and the Clark Leadership Chair in Data Analytics in the Department of Biology at the University of Maryland. Previously, he held the Tom and Marie Patton Chair in Biological Sciences at the Georgia Institute of Technology, where he founded the Interdisciplinary Graduate Program in Quantitative Biosciences. He is the author of Quantitative Viral Ecology (Princeton). Bradford P. Taylor is a research associate in the T. H. Chan School of Public Health at Harvard University.

• PrefaceThe goalYou can do itAcknowledgmentsPart I Molecular and Cellular Biosciences1 Fluctuations and the Nature of Mutations1.1 Hands-on approach to mutations and selection1.2 Sampling from provided distributions1.3 Sampling from custom distributions1.4 Comparing binomial and Poisson distributions1.5 The start of dynamics1.6 Inferring parameters from data2 Bistability of Genetic Circuits2.1 Continuous models of cellular dynamics and gene regulation2.2 Simulating coupled ordinary differential equations2.3 Qualitative analysis of nonlinear dynamical systems2.4 Evaluating the local stability of equilibria2.5 Bistability and bifurcation diagrams3 Stochastic Gene Expression and Cellular Variability3.1 Simulating stochastic gene expression3.2 Poisson processes: Finding the time of the next event3.3 A theory of timing given multiple stochastic processes3.4 Gillespie algorithm applied to a gene expression model3.5 Loading and saving data4 Evolutionary Dynamics: Mutations, Selection, and Diversity4.1 Modeling evolutionary dynamics4.2 Transition matrices in Markov processes4.3 The Wright-Fisher modelPart II Organismal Behavior and Physiology5 Robust Sensing and Chemotaxis5.1 Toward chemotaxis in single-celled organisms5.2 Enzyme kinetics5.3 Time-dependent functions in differential equations5.4 Probability distribution redux5.5 E. coli movement6 Nonlinear Dynamics and Signal Processing in Neurons6.1 Computational neuroscience6.2 The Hodgkin-Huxley model6.3 Firing without a current6.4 Neuron dynamics: Thresholds in magnitude and time6.5 Technical appendix7 Excitations and Signaling, from Cells to Tissue7.1 Excitable media: From localized to spatial dynamics7.2 FitzHugh-Nagumo: The ODE model7.3 FitzHugh-Nagumo: One-dimensional PDEs8 Organismal Locomotion through Water, Air, and Earth8.1 Introduction8.2 The internal origins of movement8.3 Orbits in configuration space8.4 From Borelli to Newton and back again8.5 The greatest gait of allPart III Populations and Ecological Communities9 Flocking and Collective Behavior: When Many Become One9.1 Agent-based models and emergence in flocks9.2 The Vicsek model9.3 Flocking dynamics9.4 Bonus: SPP and the power of leadership10 Conflict and Cooperation Among Individuals and Populations10.1 Strategies, games, and populations10.2 Mean field replicator dynamics of microbial games10.3 Stochastic versions of microbial games10.4 Type VI secretion—a killer game, in space11 Eco-evolutionary Dynamics11.1 From predation events to population dynamics11.2 Ecological dynamics when evolution is fast11.3 Functional responses—a microscopic approach12 Outbreak Dynamics: From Prediction to Control12.1 Outbreaks: From deterministic models to stochastic realizations12.2 Epidemic model—fundamentals12.3 Stochastic epidemicsPart IV The Future of Ecosystems13 Ecosystems: Chaos, Tipping Points, and Catastrophes13.1 Modeling complexity: An enabling view13.2 Small differences, big effects13.3 Explosive growth and population catastrophes13.4 Small models of a big climate13.5 CodaBibliographyIndex