Course description
This one-week course introduces the theory and practical use of biologically informed neural networks (BINNs) in the life sciences. Participants will learn how to integrate molecular networks with deep learning approaches and apply them to biological data.
Each day combines lectures with hands-on workshops, covering topics such as: translating prior biological knowledge into model structures (e.g. pathway-guided layers); training, troubleshooting, and evaluating BINNs; interpreting trained models; and reasoning about when to constrain or expand models to better reflect cellular complexity. By the end of the week, participants will be equipped with the tools to adapt a BINN template to their own research questions.
Prior to the course, concise primers on core neural-network concepts and commonly used biological datasets will be provided. Participants should bring their own laptop and have basic programming experience in Python, but no advanced knowledge of neural networks is required. The emphasis is on conceptual understanding and hands-on intuition.
Coursework will be conducted in an online notebook environment using small biological datasets and a pre-trained BINN, enabling participants to run, visualize, and interpret models. Guest lectures from researchers applying BINNs in areas such as cancer and infectious disease will provide insight into current applications and future directions.
Prerequisites and Selection
Prerequisite courses, or equivalent
No prerequisite courses, or equivalent, demanded for this course. While prior experience in areas such as bioinformatics, statistics, or deep learning can be beneficial, the course is designed to provide the necessary background for students from diverse scientific disciplines.
Selection
Selection will be based on:
1) the relevance of the course syllabus for the applicant’s individual study plan/research (according to written motivation).
2) start date of doctoral studies (priority given to earlier start date).
Course director
Course director: Avlant Nilsson
Course co-director: Xuechun Xu
Course syllabus
C5F6080
Department
Department of Cell and Molecular Biology
Doctoral programme
Cell Biology and Genetics (CBG)
Type of course
Bioinformatics
Keywords
Artificial Neural Networks, Artificiella Neuronnätverk, Machine learning, Maskininlärning