Foundation Models for Biological Data Modalities - Advances in Genomic and Protein Sequence Analysis

Watch a comprehensive research talk exploring three groundbreaking papers in biological foundation models and their applications. Delve into the potential of genomic language models (gLMs) for protein task predictions, discover ChatNT - a pioneering multimodal conversational agent for biological sequences, and learn about innovative multi-modal transfer learning approaches connecting DNA, RNA, and protein models. Join Thomas Pierrot from InstaDeep as he examines how these advanced models are revolutionizing our understanding of biological sequences, from improving protein task predictions to enabling sophisticated multi-modal analysis across different biological data types. Gain insights into cutting-edge developments in computational biology, including novel perplexity-based prediction calibration techniques and frameworks for genomics instruction-tuning that promise to advance biological research and accessibility.