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From biological data to computational models: research-informed teaching in bioinformatics, biostatistics, and health data science

Olli-Pekka Smolander
HUS Neurocenter

Abstract: My work combines computer science, statistics, biology, and medicine. The research examples in this presentation illustrate this background: I will start from stochastic modelling of biological systems at the molecular level. Next, I will walk you through genome-scale and systems-level analysis. After that, I will take you to my current clinical bioinformatics work on Parkinson’s disease microbiome data.

I will also tell you about my teaching philosophy. I believe that while students must learn to use and develop novel computational tools, they also need to understand where the data come from, recognise what assumptions models make, interpret uncertainties, and communicate computational results across disciplinary boundaries.

Furthermore, I will share you some of my teaching experiences in digital bioinformatics projects that I had with international student groups coming from diverse disciplinary backgrounds. To conclude, I will outline my future goals in teaching and research at Aalto University and describe how I combine theoretical insights with computational work to respond to the emerging technological and societal changes.

Bio: Olli-Pekka Smolander is a computational biologist and bioinformatician whose work combines bioinformatics, biostatistics, genomics, microbiome research, systems biology, and health data science. He currently works as Principal Data Scientist at HUS Neurocenter in a Parkinson’s disease research group and holds the Title of Docent in Bioinformatics at the University of Helsinki. He previously served as Professor of Bioinformatics at Tallinn University of Technology, where he taught and developed courses in bioinformatics, genomics, and high-throughput biology. He has supervised students and researchers at bachelor’s, master’s, doctoral, and postdoctoral levels. His research includes more than 50 peer-reviewed publications and computational contributions to clinical bioinformatics, molecular medicine, genomics, and microbiome research. He has published several articles at top-tier journals such as Nature Genetics, Nature, and JAMA Neurology. His higher education approach is research-based and project-oriented, aiming to help students connect computational methods with biological data for meaningful interpretation.