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Explore the evolving field of DNA foundation modeling in this comprehensive lecture that addresses the fundamental challenge of understanding how DNA sequences encode gene regulation. Trace the development of sequence-to-function models from early convolutional architectures to sophisticated long-range models, examining their practical applications in variant effect prediction and synthetic sequence design. Discover the emergence of DNA language models and their transformative applications in predicting variant effects, while learning about the critical connections between sequence-to-function modeling and DNA language modeling. Gain insights into cutting-edge approaches including the novel multimodal masked modeling framework called Nona for functional genomics, presented by a principal ML scientist from Genentech's ReLU and BRAID teams. Understand how computational methods are revolutionizing our ability to decode the regulatory information embedded in genomic sequences and their implications for advancing functional genomics research.
