Author: Bo Shen; Xiao Yi; Yaoting Sun; Xiaojie Bi; Juping Du; Chao Zhang; Sheng Quan; Fangfei Zhang; Rui Sun; Liujia Qian; Weigang Ge; Wei Liu; Shuang Liang; Hao Chen; Ying Zhang; Jun Li; Jiaqin Xu; Zebao He; Baofu Chen; Jing Wang; Haixi Yan; Yufen Zheng; Donglian Wang; Jiansheng Zhu; Ziqing Kong; Zhouyang Kang; Xiao Liang; Xuan Ding; Guan Ruan; Nan Xiang; Xue Cai; Huanhuan Gao; Lu Li; Sainan Li; Qi Xiao; Tian Lu; Yi Judy Zhu; Huafen Liu; Haixiao Chen; Tiannan Guo
Title: Proteomic and Metabolomic Characterization of COVID-19 Patient Sera Document date: 2020_4_7
ID: nifz133q_16
Snippet: The copyright holder for this preprint (which was not peer-reviewed) is . https://doi.org/10.1101/2020.04.07.20054585 doi: medRxiv preprint Table S1 . Patients labeled in red (Y-axis) 596 indicate chronic infection of viruses including HBV. (B) Study design for 597 machine learning-based classifier development for severe COVID-19 patients. 598 We first procured samples in a training cohort for proteomic and metabolomic 599 analysis. The classifie.....
Document: The copyright holder for this preprint (which was not peer-reviewed) is . https://doi.org/10.1101/2020.04.07.20054585 doi: medRxiv preprint Table S1 . Patients labeled in red (Y-axis) 596 indicate chronic infection of viruses including HBV. (B) Study design for 597 machine learning-based classifier development for severe COVID-19 patients. 598 We first procured samples in a training cohort for proteomic and metabolomic 599 analysis. The classifier was then validated in an independent cohort.
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