| Examination of independent prognostic power of gene expressions and histopathological imaging features in cancer T Zhong, M Wu, S Ma Cancers 11 (3), 361, 2019 | 20 | 2019 |
| Identification of human circadian genes based on time course gene expression profiles by using a deep learning method P Cui, T Zhong, Z Wang, T Wang, H Zhao, C Liu, H Lu Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease 1864 (6 …, 2018 | 15 | 2018 |
| Histopathological imaging-based cancer heterogeneity analysis via penalized fusion with model averaging B He, T Zhong, J Huang, Y Liu, Q Zhang, S Ma Biometrics 77 (4), 1397-1408, 2021 | 10 | 2021 |
| Histopathological imaging features-versus molecular measurements-based cancer prognosis modeling S Zhang, Y Fan, T Zhong, S Ma Scientific reports 10 (1), 15030, 2020 | 9 | 2020 |
| Histopathological imaging–environment interactions in cancer modeling Y Xu, T Zhong, M Wu, S Ma Cancers 11 (4), 579, 2019 | 6 | 2019 |
| DASAF: An R Package for Deep Sequencing‐Based Detection of Fetal Autosomal Abnormalities from Maternal Cell‐Free DNA B Liu, X Tang, F Qiu, C Tao, J Gao, M Ma, T Zhong, JP Cai, Y Li, G Ding BioMed Research International 2016 (1), 2714341, 2016 | 5 | 2016 |
| Heterogeneity analysis via integrating multi-sources high-dimensional data with applications to cancer studies T Zhong, Q Zhang, J Huang, M Wu, S Ma Statistica Sinica 33 (2), 729, 2023 | 4 | 2023 |
| Hierarchical cancer heterogeneity analysis based on histopathological imaging features M Ren, Q Zhang, S Zhang, T Zhong, J Huang, S Ma Biometrics 78 (4), 1579-1591, 2022 | 3 | 2022 |
| Evaluating coverage of exons by HapMap SNPs X Dong, T Zhong, T Xu, Y Xia, B Li, C Li, L Yuan, G Ding, Y Li Genomics 101 (1), 20-23, 2013 | 3 | 2013 |
