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Parallel Approximate Bayesian Computing Sequential Monte Carlo (pABC-SMC) algorithm for statistical inference for multi-scale and multi-cellular biological processes

Features

The pABC-SMC repository provides an implementation for the simulation of tumour spheroids. Furthermore, it facilitates the statistical inference of model parameters from spheroid growth curves and histological information. Its key features are

• efficient numerical implementation for lattice-based model for tumour spheroid growth;
• collection of experimental data for SK-MES-1 cells;
• statistical inference using Approximate Bayesian Computing Sequential Monte Carlo (ABC-SMC); and
• parallelisation using the ABC-SMC algorithm for our grid topology.

Requirements

Algorithms implemented in the pABC-SMC repository employ C++ and MATLAB. To exploit its functionality the MATLAB Statistical Toolbox. The parallel implementation is tailored for our computing grid. The use of other infrastructures requires reimplementation.