Dynamic Models In Biology Pdf

┌─────────────────────────────────────────────────────────┐ │ Dynamic Modeling Applications │ └────────────────────────────┬────────────────────────────┘ │ ┌─────────────────────┼─────────────────────┐ ▼ ▼ ▼ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ Systems Bio │ │ Epidemiology │ │ Ecology & EV │ │ & Med Chem │ │ & Public │ │ Population │ │ (PK/PD, Drug │ │ Health │ │ Dynamics │ │ Discovery) │ │ (SIR Models) │ │ (Evolution) │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ Systems Biology and Pharmacology

Dynamic models in biology are mechanistic frameworks used to understand and predict how biological systems change over time. Unlike static statistical models, they focus on the underlying causal processes—such as how a virus spreads or how a cell divides—rather than just describing patterns in data. Core Components of a Dynamic Model dynamic models in biology pdf

When biological populations or molecular counts are large, randomness averages out. Scientists use Ordinary Differential Equations (ODEs) to model these systems continuously over time. The classic Lotka-Volterra predator-prey model. Equation Shape: is predator, and 2. Stochastic Models (Probabilistic Systems) Stochastic Models (Probabilistic Systems)