Predicting Collision Cross-Section Values for Small Molecules through Chemical Class-Based Multimodal Graph Attention Network-Reference-Cited by-同舟云学术

Predicting Collision Cross-Section Values for Small Molecules through Chemical Class-Based Multimodal Graph Attention Network

Author:

Wang Cheng¹²³^ORCID,Yuan Chuang⁴⁵,Wang Yahui³⁶,Shi Yuying¹²,Zhang Tao¹²^ORCID,Patti Gary J.³⁶⁷⁸^ORCID

Affiliation:

1. Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China

2. National Institute of Health Data Science of China, Shandong University, Jinan 250000, China

3. Department of Chemistry, Washington University in St. Louis, St. Louis, Missouri 63130 United States

4. School of Life Sciences, and Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China

5. Department of Biochemistry and Biophysics, School of Basic Medical Sciences, Peking University, Beijing 100191, China

6. Department of Medicine, Washington University in St. Louis, St. Louis, Missouri 63130, United States

7. Siteman Cancer Center, Washington University in St. Louis, St. Louis, Missouri 63130, United States

8. Center for Metabolomics and Isotope Tracing, Washington University in St. Louis, St. Louis, Missouri 63130, United States

Funder

National Key Research and Development Program of China

Shandong University

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

National Institutes of Health

Publisher

American Chemical Society (ACS)

Link

Reference33 articles.