| Protein threading using residue co-variation and deep learning J Zhu, S Wang, D Bu, J Xu Bioinformatics 34 (13), i263-i273, 2018 | 75 | 2018 |
| CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction F Ju, J Zhu, B Shao, L Kong, TY Liu, WM Zheng, D Bu Nature communications 12 (1), 2535, 2021 | 68* | 2021 |
| Improving protein fold recognition by extracting fold-specific features from predicted residue–residue contacts J Zhu, H Zhang, SC Li, C Wang, L Kong, S Sun, WM Zheng, D Bu Bioinformatics 33 (23), 3749-3757, 2017 | 47 | 2017 |
| FALCON@ home: a high-throughput protein structure prediction server based on remote homologue recognition C Wang, H Zhang, WM Zheng, D Xu, J Zhu, B Wang, K Ning, S Sun, SC Li, ... Bioinformatics 32 (3), 462-464, 2016 | 45 | 2016 |
| Towards predicting equilibrium distributions for molecular systems with deep learning S Zheng, J He, C Liu, Y Shi, Z Lu, W Feng, F Ju, J Wang, J Zhu, Y Min, ... arXiv preprint arXiv:2306.05445, 2023 | 30 | 2023 |
| Improving residue–residue contact prediction via low-rank and sparse decomposition of residue correlation matrix H Zhang, Y Gao, M Deng, C Wang, J Zhu, SC Li, WM Zheng, D Bu Biochemical and biophysical research communications 472 (1), 217-222, 2016 | 26 | 2016 |
| Pre-training co-evolutionary protein representation via a pairwise masked language model L He, S Zhang, L Wu, H Xia, F Ju, H Zhang, S Liu, Y Xia, J Zhu, P Deng, ... arXiv preprint arXiv:2110.15527, 2021 | 25 | 2021 |
| Co-evolution transformer for protein contact prediction H Zhang, F Ju, J Zhu, L He, B Shao, N Zheng, TY Liu Advances in Neural Information Processing Systems 34, 14252-14263, 2021 | 15 | 2021 |
| Predicting protein inter-residue contacts using composite likelihood maximization and deep learning H Zhang, Q Zhang, F Ju, J Zhu, Y Gao, Z Xie, M Deng, S Sun, WM Zheng, ... BMC bioinformatics 20, 1-11, 2019 | 15 | 2019 |
| Improving prediction of burial state of residues by exploiting correlation among residues H Gong, H Zhang, J Zhu, C Wang, S Sun, WM Zheng, D Bu BMC bioinformatics 18, 165-175, 2017 | 12 | 2017 |
| Protein structure prediction: challenges, advances, and the shift of research paradigms B Huang, L Kong, C Wang, F Ju, Q Zhang, J Zhu, T Gong, H Zhang, C Yu, ... Genomics, Proteomics & Bioinformatics, 2023 | 9 | 2023 |
| ProALIGN: Directly learning alignments for protein structure prediction via exploiting context-specific alignment motifs L Kong, F Ju, WM Zheng, J Zhu, S Sun, J Xu, D Bu Journal of Computational Biology 29 (2), 92-105, 2022 | 4 | 2022 |
| ISSEC: inferring contacts among protein secondary structure elements using deep object detection Q Zhang, J Zhu, F Ju, L Kong, S Sun, WM Zheng, D Bu BMC bioinformatics 21, 1-13, 2020 | 4 | 2020 |
| Seq-SetNet: exploring sequence sets for inferring structures F Ju, J Zhu, G Wei, Q Zhang, S Sun, D Bu arXiv preprint arXiv:1906.11196, 2019 | 3 | 2019 |
| Seq-SetNet: directly exploiting multiple sequence alignment for protein secondary structure prediction F Ju, J Zhu, Q Zhang, G Wei, S Sun, WM Zheng, D Bu Bioinformatics 38 (4), 990-996, 2022 | 2 | 2022 |
| CREaTor: zero-shot cis-regulatory pattern modeling with attention mechanisms Y Li, F Ju, Z Chen, Y Qu, H Xia, L He, L Wu, J Zhu, B Shao, P Deng Genome Biology 24 (1), 266, 2023 | 1 | 2023 |
Haicang ZhangColumbia UniversityVerified email at cumc.columbia.edu
