المؤلفون: Zhu, Yue, Dai, Jun, Xu, Xiaopeng, Gao, Yi, Shen, Weidong, Zhang, Shuyu, Liu, Pengfei

المصدر: Radiation Medicine and Protection ; volume 4, issue 3, page 117-124 ; ISSN 2666-5557

مصطلحات موضوعية: Public Health, Environmental and Occupational Health, Radiology, Nuclear Medicine and imaging, Radiological and Ultrasound Technology, Emergency Medical Services

الإتاحة: https://doi.org/10.1016/j.radmp.2023.08.003Test
https://api.elsevier.com/content/article/PII:S2666555723000436?httpAccept=text/xmlTest
https://api.elsevier.com/content/article/PII:S2666555723000436?httpAccept=text/plainTest

المؤلفون: Chen, Xiaowei, Liao, Chentong, Deng, Min, Xu, Xiaopeng, Yu, Liyang, Li, Ruipeng, Peng, Qiang

المصدر: Chemical Engineering Journal ; volume 451, page 139046 ; ISSN 1385-8947

مصطلحات موضوعية: Industrial and Manufacturing Engineering, General Chemical Engineering, Environmental Chemistry, General Chemistry

الإتاحة: https://doi.org/10.1016/j.cej.2022.139046Test
https://api.elsevier.com/content/article/PII:S1385894722045259?httpAccept=text/xmlTest
https://api.elsevier.com/content/article/PII:S1385894722045259?httpAccept=text/plainTest

المؤلفون: Yang, Linwei, Wang, Zi-Ang, Geng, Ran, Deng, Hengwei, Niu, Shengwen, Zuo, Hongliang, Weng, Shaoping, He, Jianguo, Xu, Xiaopeng

المساهمون: Kibenge, Frederick S. B., China Agricultural Research System, MOE | Fundamental Research Funds for the Central Universities, MOST | National Key Research and Development Program of China, National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province, Science and Technology program of Guangzhou

المصدر: Microbiology Spectrum ; volume 11, issue 1 ; ISSN 2165-0497

الإتاحة: https://doi.org/10.1128/spectrum.02363-22Test

المؤلفون: Xu, Xiaopeng

مرشدي الرسالة: Gao, Xin, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, Solovyev, Victor, Bajic, Vladimir B.

مصطلحات موضوعية: flux balance analysis, stress condition, Metabolic modeling, flux variability analysis

الإتاحة: http://hdl.handle.net/10754/552665Test

المؤلفون: Xu, Xiaopeng, Li, Minghui, Xu, Wenjia, Wang, Min, Wu, Yan, Cheng, Liying, Li, Jinyang, Qin, Yang, Liu, Sha, Yang, Gangqiang, Sun, Kaoxiang, Zhang, Peng

المصدر: Molecular Pharmaceutics; 7/1/2024, Vol. 21 Issue 7, p3434-3446, 13p

المؤلفون: Xu, Xiaopeng^1,2 (AUTHOR) xin.gao@kaust.edu.sa, Xu, Chencheng^1,2 (AUTHOR), He, Wenjia^1,2 (AUTHOR), Wei, Lesong^1,2 (AUTHOR), Li, Haoyang^1,2 (AUTHOR), Zhou, Juexiao^1,2 (AUTHOR), Zhang, Ruochi³ (AUTHOR), Wang, Yu³ (AUTHOR), Xiong, Yuanpeng³ (AUTHOR), Gao, Xin^1,2 (AUTHOR) xin.gao@kaust.edu.sa

المصدر: Bioinformatics. Jun2024, Vol. 40 Issue 6, p1-9. 9p.

المؤلفون: Chen, Xuyang, Li, Yinfeng, Jing, Wenwen, Zhou, Tao, Xu, Xiaopeng, Duan, Yuwei, Yu, Liyang, Li, Ruipeng, Peng, Qiang

المصدر: Angewandte Chemie; 5/21/2024, Vol. 136 Issue 21, p1-10, 10p

مصطلحات موضوعية: SOLAR cells, SMALL molecules, POLYMER networks, PHASE separation, PHOTOVOLTAIC power systems, CHARGE carriers, MORPHOLOGY

المؤلفون: Xu, Xiaopeng, Zhou, Juexiao, Zhu, Chen, Zhan, Qing, Li, Zhongxiao, Zhang, Ruochi, Wang, Yu, Liao, Xingyu, Gao, Xin

المساهمون: Computer Science Program, Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Computational Bioscience Research Center (CBRC), KAUST Catalysis Center (KCC), Syneron Technology, Guangzhou, China

وصف الملف: application/pdf

العلاقة: github:charlesxu90/sgpt; https://chemrxiv.org/engage/chemrxiv/article-details/64272436a029a26b4cb49451Test; Xu, X., Zhou, J., Zhu, C., Zhan, Q., Li, Z., Zhang, R., Wang, Y., Liao, X., & Gao, X. (2023). Optimization of binding affinities in chemical space with generative pretrained transformer and deep reinforcement learning. https://doi.org/10.26434/chemrxiv-2023-7v4swTest; http://hdl.handle.net/10754/690881Test

الإتاحة: https://doi.org/10.26434/chemrxiv-2023-7v4swTest
https://doi.org/10.5281/zenodo.7632731Test
http://hdl.handle.net/10754/690881Test

المؤلفون: Liao, Xingyu, Zhou, Juexiao, Zhang, Bin, Li, Xingyi, Xu, Xiaopeng, Li, Haoyang, Gao, Xin

المساهمون: Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia, Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Computational Bioscience Research Center (CBRC), Computer Science Program, School of computer science, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, China

وصف الملف: application/pdf

العلاقة: github:JoshuaChou2018/DeepTR; Liao, X., Zhou, J., Zhang, B., Xu, X., Li, H., & Gao, X. (2023). Deep Learning Enhanced Tandem Repeat Variation Identification via Multi-Modal Conversion of Nanopore Reads Alignment. https://doi.org/10.1101/2023.08.17.553659Test; http://hdl.handle.net/10754/693793Test

الإتاحة: https://doi.org/10.1101/2023.08.17.553659Test
http://hdl.handle.net/10754/693793Test

المؤلفون: Xu, Xiaopeng, Li, Minghui, Xu, Wenjia, Wang, Min, Wu, Yan, Cheng, Liying, Li, Jinyang, Qin, Yang, Liu, Sha, Yang, Gangqiang, Sun, Kaoxiang, Zhang, Peng

المصدر: Molecular Pharmaceutics; July 2024, Vol. 21 Issue: 7 p3434-3446, 13p