This webpage presents an overview of resources concerned with stochastic particle methods in Biology and Chemistry.
Molecular chemistry, molecular dynamics : top eigenvalues and ground state energies.
Population dynamics, cellular dynamics, genetic models
Quasi-invariant measures, Yaglom distributions
Medical applications : food risk analysis, epidemiology
Branching and Interacting processes.
Genealogical and ancestral tree models
This list of topics is clearly far from being exhaustive, and it is partially biased towards my work on stochastic particle models.
More references and links to this subject can be added on demand. This webpage also contains some articles on the particle and sequential Monte Carlo methodology,
and the performance analysis of these algorithms.
The software BIIPS is a general software developed by the INRIA team ALEA
for bayesian inference with interacting particle systems, a.k.a. Sequential Monte Carlo methods.
A demonstration of the BiiPS software for estimating the stochastic volatility of financial data can be found in