| Predicting the potential human lncRNA–miRNA interactions based on graph convolution network with conditional random field W Wang, L Zhang, J Sun, Q Zhao, J Shuai Briefings in bioinformatics 23 (6), bbac463, 2022 | 182 | 2022 |
| Updated review of advances in microRNAs and complex diseases: taxonomy, trends and challenges of computational models L Huang, L Zhang, X Chen Briefings in bioinformatics 23 (5), bbac358, 2022 | 93 | 2022 |
| Updated review of advances in microRNAs and complex diseases: towards systematic evaluation of computational models L Huang, L Zhang, X Chen Briefings in bioinformatics 23 (6), bbac407, 2022 | 75 | 2022 |
| Prediction of potential miRNA–disease associations through a novel unsupervised deep learning framework with variational autoencoder L Zhang, X Chen, J Yin Cells 8 (9), 1040, 2019 | 72 | 2019 |
| Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion L Huang, L Zhang, X Chen Briefings in bioinformatics 23 (6), bbac397, 2022 | 71 | 2022 |
| Predicting drug–target binding affinity through molecule representation block based on multi-head attention and skip connection L Zhang, CC Wang, X Chen Briefings in bioinformatics 23 (6), bbac468, 2022 | 53 | 2022 |
| SNRMPACDC: computational model focused on Siamese network and random matrix projection for anticancer synergistic drug combination prediction TH Li, CC Wang, L Zhang, X Chen Briefings in bioinformatics 24 (1), bbac503, 2023 | 42 | 2023 |
| Differential expression and bioinformatics analysis of circRNA in non-small cell lung cancer Q Sun, X Li, M Xu, L Zhang, H Zuo, Y Xin, L Zhang, P Gong Frontiers in Genetics 11, 586814, 2020 | 38 | 2020 |
| Deciphering ligand–receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data L Peng, J Tan, W Xiong, L Zhang, Z Wang, R Yuan, Z Li, X Chen Computers in Biology and Medicine 163, 107137, 2023 | 35 | 2023 |
| GPCNDTA: prediction of drug-target binding affinity through cross-attention networks augmented with graph features and pharmacophores L Zhang, CC Wang, Y Zhang, X Chen Computers in Biology and Medicine 166, 107512, 2023 | 26 | 2023 |
| Stgnnks: identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering L Peng, X He, X Peng, Z Li, L Zhang Computers in Biology and Medicine 166, 107440, 2023 | 25 | 2023 |
| Drug–drug interaction prediction: databases, web servers and computational models Y Zhao, J Yin, L Zhang, Y Zhang, X Chen Briefings in Bioinformatics 25 (1), bbad445, 2024 | 24 | 2024 |
| Short‐Term Coalmine Gas Concentration Prediction Based on Wavelet Transform and Extreme Learning Machine W Xiang, Q Jian-sheng, H Cheng-hua, Z Li Mathematical Problems in Engineering 2014 (1), 858260, 2014 | 19 | 2014 |
| Validating HMMR Expression and Its Prognostic Significance in Lung Adenocarcinoma Based on Data Mining and Bioinformatics Methods X Li, H Zuo, L Zhang, Q Sun, Y Xin, L Zhang Frontiers in Oncology 11, 720302, 2021 | 15 | 2021 |
| RFEM: a framework for essential microRNA identification in mice based on rotation forest and multiple feature fusion SH Wang, Y Zhao, CC Wang, F Chu, LY Miao, L Zhang, L Zhuo, X Chen Computers in Biology and Medicine 171, 108177, 2024 | 11 | 2024 |
| In silico prediction of potential miRNA‐disease association using an integrative bioinformatics approach based on kernel fusion NN Guan, CC Wang, L Zhang, L Huang, JQ Li, X Piao Journal of Cellular and Molecular Medicine 24 (1), 573-587, 2020 | 9 | 2020 |
| A deep learning-based unsupervised learning method for spatially resolved transcriptomic data analysis L Peng, X He, L Zhang, X Peng, Y Lu, Z Li, X Chen 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2022 | 2 | 2022 |
| Computational models for self-interacting proteins prediction J Qu, Y Zhao, L Zhang, SB Cai, Z Ming, CC Wang Protein and Peptide Letters 27 (5), 392-399, 2020 | 2 | 2020 |
| Predicting PROTAC-targeted Degradation and Designing Androgen Receptor Degraders with AiPROTAC Li Zhang, Renhong Sun, Xia Li, Chaowei Ren, Yahui Long, Wenjuan Tan ... bioRxiv, doi: https://doi.org/10.1101/2025.02.26.640266, 2025 | | 2025 |
| An Equivariant Pretrained Transformer for Unified 3D Molecular Representation Learning W Huang, R Jiao, X Kong, L Zhang, Z Yu, F Ren, W Tan, Y Liu | | 2025 |
Xing ChenJiangnan UniversityПотвърден имейл адрес: amss.ac.cn