Novel Markov chain Monte Carlo algorithms for Bayesian inference

The research project “Novel Markov chain Monte Carlo algorithms for Bayesian inference” is an SNSF funded two-month scientific visit by Prof. Ziheng Yang (University College London, UK) to the Bioinformatics Centre of Institute for Computational sciences at ZHAW Wädenswil.

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Description

This project focuses on developing a Rust-language library (crate) that includes an efficient MCMC toolkit for implementing Bayesian phylogenetics methods. Currently, the majority state-of-the-art methods use Bayesian inference but there are still no software packages available in Rust despite its exceptional performance characteristics. Thus, the main objective of this exchange visit is to implement (1) the new ultra-efficient algorithms in the program BPP (by Ziheng Yang), and (2) similar novel MCMC algorithms in Rust as part of the new phylo Rust library crate (by Julia Pecerska). Both implementations are then tested concurrently and in close collaboration.