| How many differentially expressed genes: a perspective from the comparison of genotypic and phenotypic distances B Zhao, A Erwin, B Xue Genomics 110 (1), 67-73, 2018 | 76 | 2018 |
| DeepDISOBind: accurate prediction of RNA-, DNA-and protein-binding intrinsically disordered residues with deep multi-task learning F Zhang, B Zhao, W Shi, M Li, L Kurgan Briefings in bioinformatics 23 (1), bbab521, 2022 | 68 | 2022 |
| DescribePROT: database of amino acid-level protein structure and function predictions B Zhao, A Katuwawala, CJ Oldfield, AK Dunker, E Faraggi, J Gsponer, ... Nucleic Acids Research 49 (D1), D298-D308, 2021 | 65 | 2021 |
| DisoLipPred: accurate prediction of disordered lipid-binding residues in protein sequences with deep recurrent networks and transfer learning A Katuwawala, B Zhao, L Kurgan Bioinformatics 38 (1), 115-124, 2022 | 50 | 2022 |
| Intrinsic disorder in human RNA-binding proteins B Zhao, A Katuwawala, CJ Oldfield, G Hu, Z Wu, VN Uversky, L Kurgan Journal of Molecular Biology 433 (21), 167229, 2021 | 44 | 2021 |
| Deep learning in prediction of intrinsic disorder in proteins B Zhao, L Kurgan Computational and Structural Biotechnology Journal 20, 1286-1294, 2022 | 41 | 2022 |
| Surveying over 100 predictors of intrinsic disorder in proteins B Zhao, L Kurgan Expert Review of Proteomics 18 (12), 1019-1029, 2021 | 37 | 2021 |
| IDPology of the living cell: intrinsic disorder in the subcellular compartments of the human cell B Zhao, A Katuwawala, VN Uversky, L Kurgan Cellular and Molecular Life Sciences 78, 2371-2385, 2021 | 30 | 2021 |
| CAID prediction portal: a comprehensive service for predicting intrinsic disorder and binding regions in proteins A Del Conte, A Bouhraoua, M Mehdiabadi, D Clementel, AM Monzon, ... Nucleic Acids Research 51 (W1), W62-W69, 2023 | 29 | 2023 |
| Compositional bias of intrinsically disordered proteins and regions and their predictions B Zhao, L Kurgan Biomolecules 12 (7), 888, 2022 | 27 | 2022 |
| Comparative evaluation of AlphaFold2 and disorder predictors for prediction of intrinsic disorder, disorder content and fully disordered proteins B Zhao, S Ghadermarzi, L Kurgan Computational and Structural Biotechnology Journal 21, 3248-3258, 2023 | 20 | 2023 |
| Tutorial: a guide for the selection of fast and accurate computational tools for the prediction of intrinsic disorder in proteins L Kurgan, G Hu, K Wang, S Ghadermarzi, B Zhao, N Malhis, G Erdős, ... Nature Protocols 18 (11), 3157-3172, 2023 | 15 | 2023 |
| CLIP: accurate prediction of disordered linear interacting peptides from protein sequences using co-evolutionary information Z Peng, Z Li, Q Meng, B Zhao, L Kurgan Briefings in Bioinformatics 24 (1), bbac502, 2023 | 15 | 2023 |
| Improving prediction accuracy using decision-tree-based meta-strategy and multi-threshold sequential-voting exemplified by miRNA target prediction B Zhao, B Xue Genomics 109 (3-4), 227-232, 2017 | 15 | 2017 |
| Computational disorder analysis in ethylene response factors uncovers binding motifs critical to their diverse functions X Sun, N Malhis, B Zhao, B Xue, J Gsponer, EHA Rikkerink International Journal of Molecular Sciences 21 (1), 74, 2019 | 14 | 2019 |
| Machine learning for intrinsic disorder prediction B Zhao, L Kurgan Machine Learning in Bioinformatics of Protein Sequences: Algorithms …, 2023 | 12 | 2023 |
| Decision-tree based meta-strategy improved accuracy of disorder prediction and identified novel disordered residues inside binding motifs B Zhao, B Xue International Journal of Molecular Sciences 19 (10), 3052, 2018 | 12 | 2018 |
| Self-regulation of functional pathways by motifs inside the disordered tails of beta-catenin B Zhao, B Xue BMC genomics 17, 513-526, 2016 | 11 | 2016 |
| Analyzing aggregation propensities of clinically relevant PTEN mutants: a new culprit in pathogenesis of cancer and other PTENopathies E Palumbo, B Zhao, B Xue, VN Uversky, V Davé Journal of Biomolecular Structure and Dynamics 38 (8), 2253-2266, 2020 | 9 | 2020 |
| Significant improvement of miRNA target prediction accuracy in large datasets using meta-strategy based on comprehensive voting and artificial neural networks B Zhao, B Xue BMC genomics 20, 1-17, 2019 | 9 | 2019 |
Lukasz KurganComputer Science, Virginia Commonwealth UniversityVerified email at vcu.edu