DaDIA: Hybridizing Data-Dependent and Data-Independent Acquisition Modes for Generating High-Quality Metabolomic Data J Guo, S Shen, S Xing, T Huan Analytical Chemistry 93 (4), 2669-2677, 2021 | 42 | 2021 |
ISFrag: De Novo Recognition of In-Source Fragments for Liquid Chromatography–Mass Spectrometry Data J Guo, S Shen, S Xing, H Yu, T Huan Analytical Chemistry 93 (29), 10243-10250, 2021 | 30 | 2021 |
EVA: Evaluation of Metabolic Feature Fidelity Using a Deep Learning Model Trained With Over 25000 Extracted Ion Chromatograms J Guo, S Shen, S Xing, Y Chen, F Chen, EM Porter, H Yu, T Huan Analytical Chemistry 93 (36), 12181-12186, 2021 | 28 | 2021 |
BUDDY: molecular formula discovery via bottom-up MS/MS interrogation S Xing, S Shen, B Xu, X Li, T Huan Nature Methods 20 (6), 881-890, 2023 | 21 | 2023 |
Paramounter: Direct Measurement of Universal Parameters To Process Metabolomics Data in a “White Box” J Guo, S Shen, T Huan Analytical Chemistry 94 (10), 4260-4268, 2022 | 12 | 2022 |
JPA: Joint Metabolic Feature Extraction Increases the Depth of Chemical Coverage for LC-MS-Based Metabolomics and Exposomics J Guo, S Shen, M Liu, C Wang, B Low, Y Chen, Y Hu, S Xing, H Yu, Y Gao, ... Metabolites 12 (3), 212, 2022 | 9 | 2022 |