| MDA-SKF: similarity kernel fusion for accurately discovering miRNA-disease association L Jiang, Y Ding, J Tang, F Guo Frontiers in Genetics 9, 618, 2018 | 75 | 2018 |
| FKL-Spa-LapRLS: an accurate method for identifying human microRNA-disease association L Jiang, Y Xiao, Y Ding, J Tang, F Guo Bmc Genomics 19, 11-25, 2018 | 59 | 2018 |
| LPI-KTASLP: prediction of lncRNA-protein interaction by semi-supervised link learning with multivariate information C Shen, Y Ding, J Tang, L Jiang, F Guo IEEE Access 7, 13486-13496, 2019 | 50 | 2019 |
| BP neural network could help improve pre-miRNA identification in various species L Jiang, J Zhang, P Xuan, Q Zou BioMed research international 2016, 2016 | 50 | 2016 |
| A novel computational method for detecting DNA methylation sites with DNA sequence information and physicochemical properties G Pan, L Jiang, J Tang, F Guo International journal of molecular sciences 19 (2), 511, 2018 | 44 | 2018 |
| Discovering cancer subtypes via an accurate fusion strategy on multiple profile data L Jiang, Y Xiao, Y Ding, J Tang, F Guo Frontiers in genetics 10, 20, 2019 | 43 | 2019 |
| Identification of human microRNA-disease association via hypergraph embedded bipartite local model Y Ding, L Jiang, J Tang, F Guo Computational Biology and Chemistry 89, 107369, 2020 | 22 | 2020 |
| LightCpG: a multi-view CpG sites detection on single-cell whole genome sequence data L Jiang, C Wang, J Tang, F Guo BMC genomics 20 (1), 306, 2019 | 22 | 2019 |
| Kernel fusion method for detecting cancer subtypes via selecting relevant expression data S Li, L Jiang, J Tang, N Gao, F Guo Frontiers in genetics 11, 979, 2020 | 21 | 2020 |
| Dynamics of synthetic yeast chromosome evolution shaped by hierarchical chromatin organization S Zhou, Y Wu, Y Zhao, Z Zhang, L Jiang, L Liu, Y Zhang, J Tang, YJ Yuan National Science Review 10 (5), nwad073, 2023 | 16 | 2023 |
| Comprehensive analysis of co-mutations identifies cooperating mechanisms of tumorigenesis L Jiang, H Yu, S Ness, P Mao, F Guo, J Tang, Y Guo Cancers 14 (2), 415, 2022 | 11 | 2022 |
| A sequence-based multiple kernel model for identifying DNA-binding proteins Y Qian, L Jiang, Y Ding, J Tang, F Guo BMC bioinformatics 22, 1-18, 2021 | 11 | 2021 |
| Multi-omics data fusion via a joint kernel learning model for cancer subtype discovery and essential gene identification J Feng, L Jiang, S Li, J Tang, L Wen Frontiers in genetics 12, 647141, 2021 | 11 | 2021 |
| Predicting MHC class I binder: existing approaches and a novel recurrent neural network solution L Jiang, H Yu, J Li, J Tang, Y Guo, F Guo Briefings in Bioinformatics 22 (6), bbab216, 2021 | 8 | 2021 |
| SBSA: an online service for somatic binding sequence annotation L Jiang, F Guo, J Tang, H Yu, S Ness, M Duan, P Mao, YY Zhao, Y Guo Nucleic acids research 50 (1), e4-e4, 2022 | 7 | 2022 |
| EditPredict: prediction of RNA editable sites with convolutional neural network J Wang, S Ness, R Brown, H Yu, O Oyebamiji, L Jiang, Q Sheng, ... Genomics 113 (6), 3864-3871, 2021 | 7 | 2021 |
| SMDB: pivotal somatic sequence alterations reprogramming regulatory cascades L Jiang, M Duan, F Guo, J Tang, O Oybamiji, H Yu, S Ness, YY Zhao, ... NAR cancer 2 (4), zcaa030, 2020 | 7 | 2020 |
| Improved identification of cytokines using feature selection techniques L Jiang, Z Liao, R Su, L Wei Letters in Organic Chemistry 14 (9), 632-641, 2017 | 6 | 2017 |
| Two-stage-vote ensemble framework based on integration of mutation data and gene interaction network for uncovering driver genes Y Kan, L Jiang, Y Guo, J Tang, F Guo Briefings in Bioinformatics 23 (1), bbab429, 2022 | 4 | 2022 |
| Detecting SARS-CoV-2 and its variant strains with a full genome tiling array L Jiang, Y Guo, H Yu, K Hoff, X Ding, W Zhou, J Edwards Briefings in Bioinformatics 22 (6), bbab213, 2021 | 4 | 2021 |
