Call for Papers

We invite submissions describing innovative research at the intersection between machine learning and biologics engineering. We are specifically interested, but are not limited to, the following areas:

• Generating large molecules (e.g., proteins, antibodies, peptides, etc.) with targeted properties (e.g., binding affinity to a specific target, viscosity, aggregation, etc.)

• Foundational contributions in language models for proteins and antibodies.

• Generating screening libraries for lead optimization and identification.

• Sequence and structure based methods for predicting properties such as affinity, aggregation, etc.

• De novo design of proteins and antibodies.

• Predicting protein structure from sequences, and scalable extraction of surface-based features for downstream predictive tasks.

• Molecular fingerprints for improving predictive properties of downstream models targeting functional properties. 

• New datasets & benchmarks for biologics engineering.

We will follow the same style formatting instructions as the main ECML-PKDD conference. We consider extended abstracts submissions (up to 1 page) or short papers (up to 5 pages) excluding references. All submissions are expected to conform to the ECML-PKDD code of conduct.

The submission need not be anonymized. Submissions to the workshop should be sent to marble.ecml.workshop@gmail.com