Proteomics has long labored under a paradox: the field generates staggering volumes of data, yet its machine learning models have been starved of the kind of curated, standardized corpora that fueled the revolutions in language and vision. Now, a team led by researchers at Westlake University, Fudan University and the Shanghai Artificial Intelligence Laboratory has taken a decisive step toward closing that gap. In a study published in Nature Met…
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