| Improved protein structure prediction using predicted interresidue orientations J Yang, I Anishchenko, H Park, Z Peng, S Ovchinnikov, D Baker Proceedings of the National Academy of Sciences 117 (3), 1496-1503, 2020 | 1425 | 2020 |
| The trRosetta server for fast and accurate protein structure prediction Z Du, H Su, W Wang, L Ye, H Wei, Z Peng, I Anishchenko, D Baker, ... Nature protocols 16 (12), 5634-5651, 2021 | 510 | 2021 |
| Exceptionally abundant exceptions: comprehensive characterization of intrinsic disorder in all domains of life Z Peng, J Yan, X Fan, MJ Mizianty, B Xue, K Wang, G Hu, VN Uversky, ... Cellular and Molecular Life Sciences 72, 137-151, 2015 | 413 | 2015 |
| COACH-D: improved protein–ligand binding sites prediction with refined ligand-binding poses through molecular docking Q Wu, Z Peng, Y Zhang, J Yang Nucleic acids research 46 (W1), W438-W442, 2018 | 241 | 2018 |
| Comprehensive comparative assessment of in-silico predictors of disordered regions ZL Peng, L Kurgan Current Protein and Peptide Science 13 (1), 6-18, 2012 | 191 | 2012 |
| High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder Z Peng, L Kurgan Nucleic acids research 43 (18), e121-e121, 2015 | 176 | 2015 |
| A creature with a hundred waggly tails: intrinsically disordered proteins in the ribosome Z Peng, CJ Oldfield, B Xue, MJ Mizianty, AK Dunker, L Kurgan, ... Cellular and Molecular Life Sciences 71, 1477-1504, 2014 | 161 | 2014 |
| Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation JY Yang, ZL Peng, ZG Yu, RJ Zhang, V Anh, D Wang Journal of Theoretical Biology 257 (4), 618-626, 2009 | 142 | 2009 |
| More than just tails: intrinsic disorder in histone proteins Z Peng, MJ Mizianty, B Xue, L Kurgan, VN Uversky Molecular BioSystems 8 (7), 1886-1901, 2012 | 131 | 2012 |
| Genome‐scale prediction of proteins with long intrinsically disordered regions Z Peng, MJ Mizianty, L Kurgan Proteins: Structure, Function, and Bioinformatics 82 (1), 145-158, 2014 | 124 | 2014 |
| mTM-align: an algorithm for fast and accurate multiple protein structure alignment R Dong, Z Peng, Y Zhang, J Yang Bioinformatics 34 (10), 1719-1725, 2018 | 117 | 2018 |
| Interplay between the oxidoreductase PDIA6 and microRNA-322 controls the response to disrupted endoplasmic reticulum calcium homeostasis J Groenendyk, Z Peng, E Dudek, X Fan, MJ Mizianty, E Dufey, H Urra, ... Science signaling 7 (329), ra54-ra54, 2014 | 116 | 2014 |
| MFDp2: Accurate predictor of disorder in proteins by fusion of disorder probabilities, content and profiles MJ Mizianty, Z Peng, L Kurgan Intrinsically disordered proteins 1 (1), e24428, 2013 | 111 | 2013 |
| Prediction of protein structural classes for low-homology sequences based on predicted secondary structure JY Yang, ZL Peng, X Chen BMC bioinformatics 11, 1-10, 2010 | 108 | 2010 |
| Single-sequence protein structure prediction using supervised transformer protein language models W Wang, Z Peng, J Yang Nature Computational Science 2 (12), 804-814, 2022 | 107 | 2022 |
| Protein contact prediction using metagenome sequence data and residual neural networks Q Wu, Z Peng, I Anishchenko, Q Cong, D Baker, J Yang Bioinformatics 36 (1), 41-48, 2020 | 96 | 2020 |
| mTM-align: a server for fast protein structure database search and multiple protein structure alignment R Dong, S Pan, Z Peng, Y Zhang, J Yang Nucleic acids research 46 (W1), W380-W386, 2018 | 96 | 2018 |
| On the complementarity of the consensus-based disorder prediction Z Peng, L Kurgan Biocomputing 2012, 176-187, 2012 | 91 | 2012 |
| Improved protein structure prediction using a new multi‐scale network and homologous templates H Su, W Wang, Z Du, Z Peng, SH Gao, MM Cheng, J Yang Advanced Science 8 (24), 2102592, 2021 | 87 | 2021 |
| Prediction of disordered RNA, DNA, and protein binding regions using DisoRDPbind Z Peng, C Wang, VN Uversky, L Kurgan Prediction of Protein Secondary Structure, 187-203, 2017 | 86 | 2017 |
