JuliaCon 2020 (times are in UTC)

Computational tools for designing modular biosystems
07-29, 17:30–17:40 (UTC), Red Track

Living systems, from molecules to ecosystems, are modular, allowing us to engineer them. I develop computational tools to aid bioscience engineering with applications in health, ecology and engineering. The whole chain of modeling, knowledge and decision relies on methods from machine learning, bioinformatics and optimization. Julia has proven to be a useful language for these tasks. In this talk, I will outline how I use Julia for my research through a series of case studies.


Biological systems are intrinsically modular: proteins contain functional units, pathways are formed by linking enzymatic steps and, at the highest level, different species form a functional ecosystem. This property allows for engineering those biosystems, from designing new proteins and pathways to selecting organisms to optimize ecosystem function. In our work, we combine tools from machine learning, optimization and bioinformatics to create novel biological entities. We found Julia an excellent language that allows us to rapidly explore ideas while still maintaining computational efficiency. In this talk, we will discuss some case studies, including selecting optimal bacterial co-cultures for BAM demineralization and the design of enzybiotic proteins using Bayesian optimization.

See also: Slides (3.7 MB)

Michiel Stock is a postdoctoral researcher, studying computational intelligence for synthetic biology and ecology.