Throughout the life sciences, we routinely seek to interpret measurements and observations
using parametrized mechanistic mathematical models. A fundamental and often overlooked …

Identifying general patterns and trends underlying the impacts and dynamics of biological
invasions has proven elusive for scientists. Recently, the impact curve was proposed as a …

In this work, we:(i) review likelihood-based inference for parameter estimation and the
construction of confidence regions; and (ii) explore the use of techniques from information …

Partial differential equation (PDE) models are often used to study biological phenomena
involving movement-birth–death processes, including ecological population dynamics and …

Interpreting data using mechanistic mathematical models provides a foundation for
discovery and decision-making in all areas of science and engineering. Developing …

As alien invasive species are a key driver of biodiversity loss, understanding patterns of
rapidly changing global species compositions depends upon knowledge of invasive species …

Throughout the life sciences, biological populations undergo multiple phases of growth,
often referred to as biphasic growth for the commonly encountered situation involving two …

Abstract The Lotka–Volterra model is widely used to model interactions between two
species. Here, we generate synthetic data mimicking competitive, mutualistic and …

An enduring challenge in computational biology is to balance data quality and quantity with
model complexity. Tools such as identifiability analysis and information criterion have been …

When employing mechanistic models to study biological phenomena, practical parameter
identifiability is important for making accurate predictions across wide ranges of unseen …