NAD tagSeq reveals that NAD+-capped RNAs are mostly produced from a large number of protein-coding genes in Arabidopsis H Zhang, H Zhong, S Zhang, X Shao, M Ni, Z Cai, X Chen, Y Xia Proceedings of the National Academy of Sciences 116 (24), 12072-12077, 2019 | 69 | 2019 |
Bisphenol S induced epigenetic and transcriptional changes in human breast cancer cell line MCF-7 W Huang, C Zhao, H Zhong, S Zhang, Y Xia, Z Cai Environmental pollution 246, 697-703, 2019 | 59 | 2019 |
Predicting gene expression using DNA methylation in three human populations H Zhong, S Kim, D Zhi, X Cui PeerJ 7, e6757, 2019 | 34 | 2019 |
Arabidopsis DXO1 possesses deNADding and exonuclease activities and its mutation affects defense‐related and photosynthetic gene expression S Pan, K Li, W Huang, H Zhong, H Wu, Y Wang, H Zhang, Z Cai, H Guo, ... Journal of integrative plant biology 62 (7), 967-983, 2020 | 33 | 2020 |
SPAAC-NAD-seq, a sensitive and accurate method to profile NAD+-capped transcripts H Hu, N Flynn, H Zhang, C You, R Hang, X Wang, H Zhong, Z Chan, Y Xia, ... Proceedings of the National Academy of Sciences 118 (13), e2025595118, 2021 | 31 | 2021 |
Genetic and polygenic risk score analysis for Alzheimer's disease in the Chinese population X Zhou, Y Chen, FCF Ip, NCH Lai, YYT Li, Y Jiang, H Zhong, Y Chen, ... Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 12 (1 …, 2020 | 28 | 2020 |
Use of NAD tagSeq II to identify growth phase-dependent alterations in E. coli RNA NAD+ capping H Zhang, H Zhong, X Wang, S Zhang, X Shao, H Hu, Z Yu, Z Cai, X Chen, ... Proceedings of the National Academy of Sciences 118 (14), e2026183118, 2021 | 25 | 2021 |
Redox‐sensitive bZIP 68 plays a role in balancing stress tolerance with growth in Arabidopsis Y Li, W Liu, H Zhong, HL Zhang, Y Xia The Plant Journal 100 (4), 768-783, 2019 | 23 | 2019 |
Arabidopsis PUB2 and PUB4 connect signaling components of pattern‐triggered immunity Y Wang, Y Wu, H Zhong, S Chen, KB Wong, Y Xia New Phytologist 233 (5), 2249-2265, 2022 | 19 | 2022 |
Deep learning-based polygenic risk analysis for Alzheimer’s disease prediction X Zhou, Y Chen, FCF Ip, Y Jiang, H Cao, G Lv, H Zhong, J Chen, T Ye, ... Communications Medicine 3 (1), 49, 2023 | 16 | 2023 |
NAD tagSeq for transcriptome-wide identification and characterization of NAD+-capped RNAs X Shao, H Zhang, Z Yang, H Zhong, Y Xia, Z Cai Nature Protocols 15 (9), 2813-2836, 2020 | 15 | 2020 |
Arabidopsis EXTRA‐LARGE G PROTEIN 1 (XLG1) functions together with XLG2 and XLG3 in PAMP‐triggered MAPK activation and immunity Y Wang, H Zhang, P Wang, H Zhong, W Liu, S Zhang, L Xiong, Y Wu, ... Journal of Integrative Plant Biology 65 (3), 825-837, 2023 | 8 | 2023 |
AtHDA6 functions as an H3K18ac eraser to maintain pericentromeric CHG methylation in Arabidopsis thaliana Q Wang, X Bao, S Chen, H Zhong, Y Liu, L Zhang, Y Xia, F Kragler, M Luo, ... Nucleic Acids Research 49 (17), 9755-9767, 2021 | 8 | 2021 |
Demographics and medication use of patients with late-onset Alzheimer’s disease in Hong Kong HY Wong, H Zhong, M Zhong, X Zhou, PYC Chan, TCY Kwok, K Mok, ... Journal of Alzheimer's Disease 87 (3), 1205-1213, 2022 | 4 | 2022 |
How Long Is Enough? Exploring the Optimal Intervals of Long-Range Clinical Note Language Modeling S Cahyawijaya, B Wilie, H Lovenia, H Zhong, MQ Zhong, YYN Ip, P Fung arXiv preprint arXiv:2211.07713, 2022 | 3 | 2022 |
Blood transcriptome analysis for Alzheimer’disease in Hong Kong Chinese population H Zhong, X Zhou, Y Jiang, Y Chen, NCH Lai, EPS Tong, RMN Lo, ... Alzheimer's & Dementia 17, e056643, 2021 | 2 | 2021 |
Deep learning methods improve polygenic risk analysis and prediction for Alzheimer’s disease X Zhou, Y Chen, F Ip, Y Jiang, H Cao, H Zhong, J Chen, T Ye, Y Chen, ... Commun. Med.(Lond) 3, 49, 2021 | 2 | 2021 |
Retrospective analysis of LNM risk factors and the effect of chemotherapy in early colorectal cancer: A Chinese multicenter study C Zeng, D Xiong, F Cheng, Q Luo, Q Wang, J Huang, G Lan, H Zhong, ... BMC cancer 20, 1-9, 2020 | 2 | 2020 |
TagSeqTools: a flexible and comprehensive analysis pipeline for NAD tagSeq data H Zhong, Z Cai, Z Yang, Y Xia bioRxiv, 2020.03. 09.982934, 2020 | 2 | 2020 |
Using deep learning models to examine the biological impact of polygenic risks for Alzheimer’s disease X Zhou, FCF Ip, G Lv, Y JIANG, H Cao, H Zhong, L Chen, AKY Fu, NY Ip Alzheimer's & Dementia 19, e065377, 2023 | 1 | 2023 |