| LncFinder: an integrated platform for long non-coding RNA identification utilizing sequence intrinsic composition, structural information and physicochemical property S Han, Y Liang, Q Ma, Y Xu, Y Zhang, W Du, C Wang, Y Li Briefings in bioinformatics 20 (6), 2009-2027, 2019 | 145 | 2019 |
| Rpiter: A hierarchical deep learning framework for ncrna–protein interaction prediction C Peng, S Han, H Zhang, Y Li International journal of molecular sciences 20 (5), 1070, 2019 | 77 | 2019 |
| Long noncoding RNA identification: comparing machine learning based tools for long noncoding transcripts discrimination S Han, Y Liang, Y Li, W Du BioMed research international 2016 (1), 8496165, 2016 | 68 | 2016 |
| Classifying breast cancer subtypes using multiple kernel learning based on omics data M Tao, T Song, W Du, S Han, C Zuo, Y Li, Y Wang, Z Yang Genes 10 (3), 200, 2019 | 51 | 2019 |
| Predictive biomarkers of colorectal cancer D Ding, S Han, H Zhang, Y He, Y Li Computational biology and chemistry 83, 107106, 2019 | 50 | 2019 |
| Capsule-LPI: a lncRNA–protein interaction predicting tool based on a capsule network Y Li, H Sun, S Feng, Q Zhang, S Han, W Du BMC bioinformatics 22 (1), 246, 2021 | 42 | 2021 |
| Long noncoding RNA and protein interactions: from experimental results to computational models based on network methods H Zhang, Y Liang, S Han, C Peng, Y Li International journal of molecular sciences 20 (6), 1284, 2019 | 36 | 2019 |
| Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts M Shi, S Han, K Klier, G Fobo, C Montrone, S Yu, M Harada, AK Henning, ... Cardiovascular Diabetology 22 (1), 141, 2023 | 23 | 2023 |
| TIGER: technical variation elimination for metabolomics data using ensemble learning architecture S Han, J Huang, F Foppiano, C Prehn, J Adamski, K Suhre, Y Li, ... Briefings in bioinformatics 23 (2), bbab535, 2022 | 23 | 2022 |
| Predicting lncRNA-disease associations using network topological similarity based on deep mining heterogeneous networks H Zhang, Y Liang, C Peng, S Han, W Du, Y Li Mathematical biosciences 315, 108229, 2019 | 19 | 2019 |
| Lncident: a tool for rapid identification of long noncoding RNAs utilizing sequence intrinsic composition and open reading frame information S Han, Y Liang, Y Li, W Du International Journal of Genomics 2016 (1), 9185496, 2016 | 18 | 2016 |
| Deep forest ensemble learning for classification of alignments of non-coding RNA sequences based on multi-view structure representations Y Li, Q Zhang, Z Liu, C Wang, S Han, Q Ma, W Du Briefings in Bioinformatics 22 (4), bbaa354, 2021 | 11 | 2021 |
| Identification and functional inference for tumor-associated long non-coding RNA Y Li, Y He, S Han, Y Liang IEEE/ACM transactions on computational biology and bioinformatics 16 (4 …, 2017 | 11 | 2017 |
| De novo Prediction of Moonlighting Proteins Using Multimodal Deep Ensemble Learning Y Li, J Zhao, Z Liu, C Wang, L Wei, S Han, W Du Frontiers in Genetics 12, 630379, 2021 | 10 | 2021 |
| LPInsider: a webserver for lncRNA–protein interaction extraction from the literature Y Li, L Wei, C Wang, J Zhao, S Han, Y Zhang, W Du BMC bioinformatics 23 (1), 135, 2022 | 5 | 2022 |
| LION: an integrated R package for effective prediction of ncRNA–protein interaction S Han, X Yang, H Sun, H Yang, Q Zhang, C Peng, W Fang, Y Li Briefings in Bioinformatics 23 (6), bbac420, 2022 | 3 | 2022 |
| Prediction of Myocardial Infarction Using a Combined Generative Adversarial Network Model and Feature-Enhanced Loss Function S Yu, S Han, M Shi, M Harada, J Ge, X Li, X Cai, M Heier, G Karstenmüller, ... Metabolites 14 (5), 258, 2024 | 2 | 2024 |
| Metabolic effects of SGLT2i and metformin on 3-hydroxybutyric acid and lactate in db/db mice M Harada, S Han, M Shi, J Ge, S Yu, J Adam, J Adamski, MF Scheerer, ... International Journal of Biological Macromolecules 265, 130962, 2024 | 2 | 2024 |
| Sure: screening unlabeled samples for reliable negative samples based on reinforcement learning Y Li, H Sun, W Fang, Q Ma, S Han, R Wang-Sattler, W Du, Q Yu Information Sciences 629, 299-312, 2023 | 2 | 2023 |
| Predicting the Ordering of Characters in Japanese Historical Documents A Lamb, T Clanuwat, S Han, M Bober-Irizar, A Kitamoto arXiv preprint arXiv:2106.06786, 2021 | 2 | 2021 |