In our subgroup, we specifically focus on non-conventional computing for understanding biological systems, including stochastic and differential programming, evolutionary computing, and other related approaches. Though we have an interest in various application fields within the applied biological sciences, we have plant growth and synthetic biology as our key focuses.
Hyperdimensional computing: a fast, robust and interpretable paradigm for biological data M. Stock, W. Van Criekinge, D. Boeckaerts, P. Dewulf, S. Taelman, M. Van Haeverbeke and B. De Baets (2024) PLOS COMPUTATIONAL BIOLOGY. 20, e1012426
https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2023.1299208/full M. Stock, O. Pieters, T. De Swaef and F. wyffels (2024) FRONTIERS IN PLANT SCIENCE. 14, 1299208.
Open-endedness in synthetic biology: A route to continual innovation for biological design M. Stock and T. E. Gorochowski (2024) SCIENCE ADVANCES. 10, eadi3621.