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This paper proposes a bio-inspired deep learning framework for accurate odor mixture perception, achieving 92.2% accuracy and providing a generalizable solution to mixture perception challenges.
GraphNOSE is an open-source graph transformer framework that predicts multi-label odor descriptors from molecular structures, achieving superior performance over existing methods with fewer parameters and improved generalization to out-of-distribution compounds.
A study from Rockefeller University reveals that fruit flies track odor plumes by edge tracking rather than the traditional surge-and-cast model, using a virtual reality treadmill to map their behavior.
An article exploring the prevalence and impact of smell disorders like anosmia, especially after Covid-19, and the growing evidence linking smell to brain health.