Machine Learning for Biomedical Research

The impact that machine learning is having in biomedical research is unprecedented. Machine learning applications enable us to mine, analyze and model biomedical data thus enriching our understanding of human diseases. The significant advances in biomedical research brought about by machine learning go along with new challenges encompassing the integration of heterogeneous sources of information, the different levels of granularity of the data, and the complexity and explainability of the models.

The Machine Learning for Biomedical Research Unit applies machine learning to biomedical problems generating resources and tools for biomedical research and secondary use of the data. The Unit is focused on providing support in projects related to machine learning spanning several areas of application, including precision medicine, genomics, and systems biology. To achieve extreme scale and high performance of our applications, we account for the use of high-performance computing and the collaboration with specialized groups at BSC.

The Unit provides consultancy and technical advice in machine learning applications for the Life Sciences Department. Furthermore, it develops its own projects and collaborations inside and outside the BSC, such as the BSC Bioinfo4Women initiative and the ELIXIR Machine Learning Focus Group. The Unit is also involved in training and dissemination activities.