About
Rui Pinto Borges is a Lecturer in Statistics at the School of Mathematics and Statistics, University of St Andrews, UK. His research bridges statistical methodology with evolutionary genomics, focusing on the development of Bayesian models to understand population dynamics, selection, and phylogenetic relationships. He is actively involved in interdisciplinary research with applications in molecular evolution and biodiversity.
Research Interests: Dr. Borges specializes in computational and statistical approaches to evolutionary questions. His work emphasizes Bayesian inference for genomic data, particularly in estimating effective population sizes, detecting selection in experimental evolution, and modeling codon usage and phylogenetic signal. He integrates high-throughput sequencing data with mathematical models to uncover evolutionary forces shaping genomes.
The recent articles reflect a strong trend in developing and applying Bayesian frameworks to problems in population and molecular evolution. Key themes include selection detection in evolve-and-resequence experiments, phylogenetic inference under uncertainty, and modeling mutational processes across species. These works are published in leading journals such as Molecular Biology and Evolution, Methods in Ecology and Evolution, and Bioinformatics, demonstrating both methodological innovation and biological relevance.
Scientific Contributions:
- Development of Bait-ER: a fully Bayesian tool for selection coefficient estimation.
- Creation of Bayesian estimators for effective population size under complex mutation models.
- Contributions to polymorphism-aware phylogenetic modeling in RevBayes.
Advising and Grants: While no direct students are listed, Dr. Borges collaborates extensively with research teams, particularly within projects led by Prof. Carolin Kosiol. He has contributed to multiple funded research projects supported by BBSRC and The Royal Society, focusing on selection modeling and time-series genomic analysis.
Labs and Teams: He is affiliated with a research group at the University of St Andrews working on statistical genomics and evolutionary modeling, contributing to open-source tools and datasets hosted on Zenodo. His work is part of a broader network in computational evolutionary biology with national and international collaborations.
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