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Wish you could do fast and more useful interpretation of large models like AlphaGenome? How can we tell what a deep learning model has learned? Ruchir Rastogi and Valeh Amiri from the Kundaje lab at Stanford walk through the main ways to interpret sequence-to-function models: in silico mutagenesis, gradient x input, integrated gradients, Shapley values, DeepSHAP and DeepLIFT. They explain why each method gives the answer it does (saturation, the role of a reference..), and how their work with Salil Deshpande extends DeepLIFT to virtually any deep learning architecture, including state-of-the-art transformer-based models such as AlphaGenome: by decomposing modules into simple primitives or by using local integrated gradients.

How do DNA foundation models help us understand DNA at scale? In this video, I discuss how modern sequence-to-function DNA models can uncover biological meaning from genomic sequence with our guests Alejandro Buendia and Danila Bredikhin from Anshul Kundaje’s lab at Stanford. We also discuss their PyTorch reimplementation of the foundational DNA sequence-to-function model, AlphaGenome, that makes it easier for the community to use and build on. This work is featured through genomicsxai, a peer-reviewed blog-style alternative to traditional publishing. Linksgenomicsxai: https://genomicsxai.github.ioAlphaGenome in PyTorch: https://genomicsxai.github.io/blogs/2...scverse: https://scverse.org

In the age of AI and virtual cells, what do model organisms such as C. elegans still have to offer? In this video, I speak with Dr. David Sherwood, Professor and Associate Chair of Biology at Duke University, about why worms remain a powerful system for biological discovery. We discuss the unique advantages of C. elegans, including its rapid life cycle, transparency, genetic tractability, invariant cell lineage with the fate of every somatic cell mapped, and that it is the only organism with a completely mapped neural connectome. We also explore how the Sherwood Lab uses genome editing, genetics, and live imaging to study the fascinating biology of basement membranes, including anchor cell invasion, a process with important parallels to invasive behavior in cancer.