Abstract: Immunotherapies have achieved remarkable success in treating hematological cancers, yet the solid tumor microenvironment remains a significant barrier to therapeutic breakthroughs. Machine learning (ML)-driven computational protein design offers a powerful approach to creating novel protein components tailored for specific functions. By combining ML-driven design with synthetic biology and immuno-engineering, we have developed innovative tools […]
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![]() Humans and other animals do not always choose the most rewarding course of action, even when we have ample time and computational resources. Why do we make mistakes? The noiseLab uses a combination of theoretical, behavioral, and neurobiological techniques to address this question. In this talk, Dr. Becket Ebitz will discuss converging evidence that mistakes are the product of representational and temporal nonlinearities in neural activity that constrain our ability to make good decisions. The talk will argue that some of these nonlinearities have long-term adaptive benefits, even when they fail to produce the best decision in the moment. |
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Abstract: Neurological conditions are the leading cause of illness worldwide, though over 92% of clinically tested CNS drug candidates fail to become treatments. Contributing to this high failure rate is a lack of understanding of human disease mechanisms, technologies to address them, and the restrictive blood-brain barrier (BBB), which most compounds fail to cross. New […] |
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