Multi-level Approximate Bayesian Computation

Abstract

1. Introduction 1. Introduction 2. Inference for stochastic... 3. Multi-level Approximate... 4. Case studies 4.1 Case study 1:... 4.2 Case study 2:... 4.3 Discussion References Well-designed mechanistic models can provide insights into biological networks that are im-perceptible to machine learning techniques. For example, where suitable experimental data exists, mechanistic models can often provide strong evidence for the causative relationships that underpin a given biological model [1]. Mechanistic, multi-scale models have been able to assimilate physical features and behaviours that span multiple time- and spatial-scales [2].\n\nTo draw reliable conclusions from a mechanistic model, experimental data are often used to inform the pla ...