Professor of Bioinformatics and Scientific Director of the SFI Centre for Research Training in Genomics Data Science. After an undergraduate degree in Theoretical Physics, Cathal Seoighe was awarded a PhD in Molecular EvolutionBioinformatics in 2000, under the supervision of Ken Wolfe in Trinity College Dublin. Later that year he went to Cape Town, South Africa, working initially with the South African Medical Research Council on a national biotechnology strategy and at the South African National Bioinformatics Institute (SANBI), University of the Western Cape (UWC), as director of Bioinformatics training. In 2001 he began working full-time as a lecturer at UWC, before joining the University of Cape Town (UCT) in 2004 as Associate Professor. He returned to Ireland in 2009 as Stokes Professor of Bioinformatics in the School of Mathematics, Statistics and Applied Mathematics at NUI Galway. Although now motivated primarily by biological problems, he has a long-standing interest in the intersection of the mathematical and biological sciences. In Cape Town he was involved in the establishment of the South African Centre for Epidemiological Modeling and Analysis (Sacema) and the African Institute of Mathematical Sciences (AIMS), representing UWC on the inaugural executive committee of the latter. Current research interests include rates and patterns of somatic mutation, probabilistic models of molecular evolution, transcriptomics and cancer genomics. He is interested in the development of methods to analyze gene expression and mRNA splicing and in understanding the impact of mutations on gene expression, particularly how human mutations responsible for complex diseases can lead to widespread perturbations of gene expression patterns.

Modeling molecular biological data, including gene expression, alternative mRNA splicing and the evolution of viruses, in particular HIV-1. In addition to computational biology research my group collaborates with lab-based scientists within and outside NUI Galway. Application areas include epigenetics of colon cancer and the DNA damage response, genome assembly and annotation and applications of next-generation genomics in developmental biology.

Cancer genomics

Probabilistic models

Deep learning for genomics