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Describing the evolution of genomes through Bayesian models

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About this event

What to expect

Explore the computational foundations of evolutionary genomics in this virtual seminar examining how Bayesian models help us understand genetic evolution across species. Presented by Leonardo de Oliveira Martins, a Tenure Track Fellow in the Department of Electrical Engineering and Electronics at the University of Liverpool, this session unpacks the statistical challenges of reconstructing multi-gene phylogenetic trees under uncertainty.

What You'll Learn

Every living organism contains thousands of genes, many of which have corresponding versions across different species. Each gene family has its own evolutionary history—its phylogeny—typically represented as a tree structure. But when you're working with whole genomes containing thousands of genes, you end up with thousands of potentially conflicting trees. This seminar addresses a fundamental question: how do we reconcile this variability and extract reliable biological insights?

Dr. de Oliveira Martins will demonstrate how Bayesian computational approaches can model biological information to reduce estimation uncertainty in multi-gene phylogenetic analysis. You'll discover why understanding this variability matters for practical applications including antibiotic resistance research, pathogen surveillance, and One Health initiatives that span microbial and biomedical domains.

Who Should Attend

This talk is ideal for researchers, data scientists, and computational biologists working at the intersection of statistics, machine learning, and life sciences. Whether you're developing statistical models for biological data, working in epidemiology, or interested in how AI and computational methods are transforming genomics research, this session offers valuable perspectives on handling uncertainty in large-scale biological datasets.

About the Speaker

Leonardo de Oliveira Martins specializes in Bayesian computational biology with a focus on evolutionary genomics and statistical modelling under uncertainty. His research encompasses both theoretical advances in phylogenetic methods and practical engineering solutions for analyzing and sharing One Health data across multiple domains.

Event Format

This virtual seminar runs from 15:00 to 17:00 GMT, allowing time for both presentation and Q&A. As part of the Liverpool Virtual Seminar Series on Data Intensive Science, it brings together researchers exploring

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