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Updated: Mar 4, 2026

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
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Published on: September 2, 2020

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无碰撞的摩根指纹:一种原则性的方法来提高机器学习性能和化学中的可解释性

Jibai Li1, Xintong Qu1, Wenlong Zhang2

  • 1Department of Environmental Science, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, 200241, People's Republic of China.

Journal of cheminformatics
|March 2, 2026
PubMed
概括

无碰撞的摩根指纹 (CF-MF) 解决了标准分子表示中的位碰撞缺陷,提高了AI模型的准确性和化学解释性. 这确保了更可靠的AI用于药物发现和材料科学.

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