| Prediction of antimicrobial resistance based on whole-genome sequencing and machine learning Y Ren, T Chakraborty, S Doijad, L Falgenhauer, J Falgenhauer, ... Bioinformatics 38 (2), 325-334, 2022 | 81 | 2022 |
| Multi-label classification for multi-drug resistance prediction of Escherichia coli Y Ren, T Chakraborty, S Doijad, L Falgenhauer, J Falgenhauer, ... Computational and Structural Biotechnology Journal 20, 1264-1270, 2022 | 18 | 2022 |
| Regulatory association of long noncoding RNAs and chromatin accessibility facilitates erythroid differentiation Y Ren, J Zhu, Y Han, P Li, J Wu, H Qu, Z Zhang, X Fang Blood advances 5 (23), 5396-5409, 2021 | 13 | 2021 |
| Deep transfer learning enables robust prediction of antimicrobial resistance for novel antibiotics Y Ren, T Chakraborty, S Doijad, L Falgenhauer, J Falgenhauer, ... Antibiotics 11 (11), 1611, 2022 | 8 | 2022 |
| Research advance and application in the gene therapy of gene editing technologies YX Ren, RD Xiao, XM Lou, XD Fang Yi Chuan= Hereditas 41 (1), 18-27, 2019 | 8 | 2019 |
| The dynamic interactive network of long non-coding RNAs and chromatin accessibility facilitates erythroid differentiation Y Ren, J Zhu, Y Han, P Li, H Qu, Z Zhang, X Fang bioRxiv, 2021.03. 02.433076, 2021 | 3 | 2021 |
| Long noncoding RNA PCED1B-AS1 promotes erythroid differentiation coordinating with GATA1 and chromatin remodeling J Zhu, Y Ren, Y Han, T Jin, Y Li, X Ruan, H Qu, S Huang, Z Zhang, X Fang Blood Science 1 (02), 161-167, 2019 | 3 | 2019 |
| Predicting hosts and cross-species transmission of Streptococcus agalactiae by interpretable machine learning Y Ren, C Li, DN Sapugahawatte, C Zhu, S Spänig, D Jamrozy, J Rothen, ... Computers in Biology and Medicine 171, 108185, 2024 | 2 | 2024 |
