Machine Learning versus Statistical Inference in Microbial Genomics

My talk given today at the 2025 Microbiology Society Conference in Liverpool:

Abstract

The advent of vast genomic datasets has transformed microbiology, presenting opportunities and challenges for data analysis. The distinct philosophies of machine learning (ML) and statistical inference gives them complementarity strengths and weaknesses in tackling big data problems in pathogen research. While statistical inference prioritizes understanding underlying relationships, ML focuses on optimizing predictive performance. In this talk I will contrast the approaches and offer a view on their relative utility for three problems: source attribution, bacterial genome-wide association studies, and predicting antimicrobial resistance phenotypes from whole genome sequences.

Announcing ProbGen22 in Oxford 28-30 March

The organizing committee is pleased to announce the 7th Probabilistic Modeling in Genomics Conference (ProbGen22) to be held at the Blavatnik School of Government and Somerville College Oxford from 28th-30th March 2022.

The meeting will be a hybrid in-person and online event. Talk sessions will feature live speakers, both in-person and online, and will take place during the afternoons (making live attendance feasible for US timezones). Talks will be recorded and made available to registrants for a period of one month. Poster sessions will be held online during the evenings.

The conference will cover probabilistic models, algorithms, and statistical methods across a broad range of applications in genetics and genomics. We invite abstract submissions on a range of topics including population genetics, natural selection, Quantitative genetics, Methods for GWAS, Applications to cancer and other diseases, Causal inference in genetic studies, Functional genomics, Assembly and variant identification, Phylogenetics, Single cell 'omics, Deep learning in genomics and Pathogen genomics.

The registration deadline is 28th February 2022.

For more details visit the conference website.