| Accurate protein function prediction via graph attention networks with predicted structure information B Lai, J Xu Briefings in Bioinformatics 23 (1), bbab502, 2022 | 50 | 2022 |
| A deep se (3)-equivariant model for learning inverse protein folding M McPartlon, B Lai, J Xu BioRxiv, 2022.04. 15.488492, 2022 | 28 | 2022 |
| End-to-End deep structure generative model for protein design B Lai, M McPartlon, J Xu bioRxiv, 2022.07. 09.499440, 2022 | 10 | 2022 |
| Annotating functional effects of non-coding variants in neuropsychiatric cell types by deep transfer learning B Lai, S Qian, H Zhang, S Zhang, A Kozlova, J Duan, J Xu, X He PLoS Computational Biology 18 (5), e1010011, 2022 | 7* | 2022 |
| Deploying synthetic coevolution and machine learning to engineer protein-protein interactions A Yang, KM Jude, B Lai, M Minot, AM Kocyla, CR Glassman, D Nishimiya, ... Science 381 (6656), eadh1720, 2023 | 6 | 2023 |
| DeepGWAS: Enhance GWAS Signals for Neuropsychiatric Disorders via Deep Neural Network Y Li, J Wen, G Li, J Chen, Q Sun, W Liu, W Guan, B Lai, J Szatkiewicz, ... Research Square, 2023 | 4 | 2023 |
| Antibody Humanization via Protein Language Model and Neighbor Retrieval H Zou, R Yuan, B Lai, Y Dou, L Wei, J Xu bioRxiv, 2023.09. 04.556278, 2023 | 2 | 2023 |
| Dynamics of biomimetic electronic artificial neural networks HM Hastings, OI Hernandez, L Jiang, B Lai, L Tensen, J Yang Proceedings of the 4th International Conference on Applications in Nonlinear …, 2017 | 1 | 2017 |
| Reversing Transcriptome-Wide Association Studies to improve expression Quantitative Trait Loci associations J Yuan, B Lai, I Pe’er bioRxiv, 2020.12. 27.424460, 2020 | | 2020 |
| A semi-supervised deep neural network method to predict deleteriousness of missense mutations B Lai, J Long, H Qi, E Gao, Y Shen Neural Information Processing Systems (NIPS) Workshop on Machine Learning in …, 2017 | | 2017 |
Jinbo XuProfessor, Toyota Technological Institute at ChicagoE-mailová adresa ověřena na: ttic.edu
