Research Overview

At MathBioLab, we develop and apply mathematical and computational approaches to understand complex biological systems.

Core Research Areas

Mathematical Modeling

We develop mathematical models to describe biological processes at various scales, from molecular interactions to population dynamics.

Computational Genomics

We utilize high-throughput genomic and transcriptomic data to understand gene regulation, in Apicomplexan parasites and cancer.

Machine Learning in Biology

We apply and develop machine learning techniques to extract insights from biological data and predict outcomes of biological processes.

Systems Biology

We study biological systems as integrated networks, examining how components interact to produce emergent properties.

Interdisciplinary Approach

Our research is inherently interdisciplinary, combining expertise from: - Mathematics and Statistics - Computer Science - Molecular Biology - Genetics and Genomics - Systems Biology