Statistics and Risk Management Seminar & Thematic Line MatHBioS (Mathematics for Health and BioSciences)

Department of Mathematics, NOVA MATH/FCT NOVA

Title: Remodelling Selection to overcome Selective Depletion Biases

Speaker: Gabriela Gomes, University of Strathclyde and NOVA Math

Date | Time: July 10, 2025 | 14:30

Location: VIII-3.4

Abstract: Every population consists of individuals that vary in many traits, and each trait may or may not be associated with fitness. Variation in fitness traits lends population studies prone to selective depletion biases. When an ageing cohort exhibits declining mortality, it could be individuals becoming healthier or selective depletion of the frail. In an epidemic, when growth in cumulative infections decelerates, it could be individuals cautiously changing behaviour or selective depletion of the most susceptible. In microbial populations, when an isogenic population is stressed by antimicrobial treatment and some cells survive, this could be due to individual cells switching between normal and persister phenotypes or antibiotic selectively killing cells that divide faster. In each case, the first explanation invokes individuals changing (1), while the second posits selection on pre-existing variation changing (2). While explanations of type (1) are intuitive and widely adopted, those of type (2) are more neutral and rarely considered due to cognitive biases and challenges in estimating all variation that matters. While both are plausibly operating in most real systems, neglect of (2) leads to over-attribution of results to (1), wrong predictions, bad policy decisions and poor reproducibility, negatively impacting science, economics and ethics. To overcome this selective depletion bias, I have been proposing a pragmatic approach to study design and analysis whereby we infer distributions of characteristics that respond to selection and reframe theories accordingly. The approach is based on remodelling selection (mathematically by introducing key parametric distributions into population dynamic models, and empirically by measuring quantities of interest along selection gradients) and statistical inference (by fitting mathematical models to data). The procedure is being tested in systems where trait distributions can be inferred from population trends as well as reconstructed directly from individual measurements. Results of this ongoing research will be presented, and the wider applicability discussed. 
Prospects for conducting some of this research at NOVA School of Science and Technology are being assessed. Please join the discussion if you find the topic interesting…

Short Bio: Gabriela Gomes graduated in Applied Mathematics from the University of Porto in 1987 and completed her MSc and PhD in Mathematics from the University of Warwick in 1990 and 1993, respectively. In 1999, she switched to biology with a Wellcome Research Training Fellowship in Mathematical Biology. In 2002, she established an independent research group at the Gulbenkian Science Institute (IGC), initially supported by a Marie Curie Excellence Grant, with a spectrum of projects ranging from fundamental mathematical concepts to the management of population and ecosystem health, public engagement in science and development of research infrastructures. She subsequently led research programmes in the Research Centre for Biodiversity and Genetic Resources (CIBIO-InBIO), the Liverpool School of Tropical Medicine (LSTM), and is now a Professor of Mathematics and Statistics at the University of Strathclyde. Gabriela in a member of NOVA Math since 2023 where she leads the participation of the centre in the European project Inno4Vac (Innovations to accelerate vaccine development and manufacture).

Gabriela Gomes has published around 100 peer-reviewed research papers in international journals, initially in Mathematics and Physics and later in Biology, Ecology and Epidemiology. She has been a member of Editorial Boards for Nature Scientific Reports, Journal of Mathematical Biology and Journal of Theoretical Biology, and integrated the Board of Directors of the Portuguese Mathematical Society twice. She held various visiting positions in the USA and Brazil and is a Fellow of the Institute of Mathematics and its Applications (FIMA) in the UK.

Organizers: Isabel Natário and Paula Patrício

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This work is funded by national funds through the FCT – Fundação para a Ciência e a Tecnologia, I.P., under the scope of the projects UIDB/00297/2020 (https://doi.org/10.54499/UIDB/00297/2020) and UIDP/00297/2020 (https://doi.org/10.54499/UIDP/00297/2020) (Center for Mathematics and Applications)

Room 1, Building XI
 
Abstract:
We provide a brief introduction to (C1,C2)-clonoids, which are sets of functions of several arguments closed under right composition with a clone C1 and under left composition with another clone C2. Our primary focus is on clonoids of Boolean functions, and we present classifications of (C1,C2)-clonoids in the spirit of Post's classification of clones. Moreover, we propose refinements and strengthenings to Sparks's theorem on the cardinalities of clonoid lattices.

More information is available here.

Venue: office 410, 4th floor of the "Departamento de Engenharia Mecânica e Industrial (DEMI)" Building

More information is available here.

Venue: office 410, 4th floor of the "Departamento de Engenharia Mecânica e Industrial (DEMI)" Building

More information is available here.

Venue: office 410, 4th floor of the "Departamento de Engenharia Mecânica e Industrial (DEMI)" Building

More information is available here.

Venue: office 410, 4th floor of the "Departamento de Engenharia Mecânica e Industrial (DEMI)" Building

More information is available here.

Venue: office 410, 4th floor of the "Departamento de Engenharia Mecânica e Industrial (DEMI)" Building

Venue: office 410, 4th floor of the "Departamento de Engenharia Mecânica e Industrial (DEMI)" Building

Venue: office 410, 4th floor of the "Departamento de Engenharia Mecânica e Industrial (DEMI)" Building

Venue: office 410, 4th floor of the "Departamento de Engenharia Mecânica e Industrial (DEMI)" Building

Venue: office 410, 4th floor of the "Departamento de Engenharia Mecânica e Industrial (DEMI)" Building