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Explore the intricacies of gene regulatory networks (GRNs) in this comprehensive 1 hour 45 minute talk by Matthew Aguirre from Valence Labs. Delve into the challenges and opportunities presented by key GRN properties such as hierarchical structure, modular organization, and sparsity. Learn about a novel approach to simulate GRN structure and model their function using stochastic differential equations. Discover insights from a systematic analysis of gene knockout effects within and across GRNs, and how these findings relate to recent genome-scale perturbation studies. Investigate potential methods for mapping gene expression regulation architecture using data from perturbed and unperturbed cell states. The talk covers background information, key graph properties, gene expression modeling, and the speaker's contributions to the field, followed by a Q&A session. Access the related research paper and connect with the AI for drug discovery community through the provided Portal link.