Speaker: Natalia Pinto Estéban.
Abstract: Machine learning is growing in significance across various research domains. One of these domains is biology, specifically focusing on protein engineering and directed evolution techniques. This presentation is grounded in the FLIP paper (Fitness Landscape Inference for Proteins), where protein functionality prediction tasks are introduced for diverse landscapes. Different baseline algorithms are trained and evaluated using various datasets, which involve amino acids sequences and protein mutations. Furthermore, diverse experiments and results based on this paper are showcased as part of the final degree project development.