“The application of artificial intelligence is the next big step to discover new ground in our massive biomedical data sets. We have to make use of this disruptive technology now”, says Prof. Dr. Martin Hrabĕ de Angelis, director at the Helmholtz Center Munich and coordinator of the pan-European project “INFRAFRONTIER”.

How can Machine Learning (ML) advance the study of genetic diseases using the enormous resource of mouse phenotyping data from the International Mouse Phenotyping Consortium (IMPC) and other data sources? To answer this question, some of the leading bioinformaticians from Europe and USA came together in Munich for the first INFRAFRONTIER/IMPC Machine Learning Hackathon.

The main objectives of the hackathon were:

• to provide an open, cooperative space for innovative ideas to apply ML methods in the context of IMPC and INFRAFRONTIER data and resources
• to find common approaches for building functional prototypes and
• to create a network of researchers interested in setting up future collaborations.

They were supported by Prof. Tudor Oprea from the University of New Mexico and principal investigator of the NIH-funded program Illuminating the Druggable Genome (IDG) https://druggablegenome.net. Prof. Oprea gave a highly informative insight on ML algorithms that are used in the pharmaceutical industry to efficiently develop novel drugs. He also instructed the participants on how to integrate data from different biological databases to predict gene function.

After the introductory talks that pitched several interesting ideas for ML applications, the 20 bioinformatics specialists split up into working groups to efficiently tackle these issues. These expert groups led a cooperative and coordinated effort to come up with intelligent and feasible ML-based solutions. Overall, significant headway was made in applying ML in gene cluster, X-ray image and the IMPC data analysis.