| Opportunities And Obstacles For Deep Learning In Biology And Medicine T Ching, DS Himmelstein, BK Beaulieu-Jones, AA Kalinin, BT Do, ... J R Soc Interface 15 (141), 2018 | 2747 | 2018 |
| Template-based protein structure modeling using the RaptorX web server M Källberg, H Wang, S Wang, J Peng, Z Wang, H Lu, J Xu Nature protocols 7 (8), 1511-1522, 2012 | 2019 | 2012 |
| Accurate de novo prediction of protein contact map by ultra-deep learning model S Wang, S Sun, Z Li, R Zhang, J Xu PLoS computational biology 13 (1), e1005324, 2017 | 1138 | 2017 |
| Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model S Wang, S Sun, Z Li, R Zhang, J Xu PLOS Computational Biology 13 (1), e1005324, 2017 | 1138 | 2017 |
| Protein secondary structure prediction using deep convolutional neural fields S Wang, J Peng, J Ma, J Xu Scientific reports 6, 2016 | 1032 | 2016 |
| Global alignment of multiple protein interaction networks with application to functional orthology detection R Singh, J Xu, B Berger Proceedings of the National Academy of Sciences 105 (35), 12763-12768, 2008 | 884 | 2008 |
| RaptorX-Property: a web server for protein structure property prediction S Wang, W Li, S Liu, J Xu Nucleic acids research 44 (W1), W430-W435, 2016 | 668 | 2016 |
| Predicting the clinical impact of human mutation with deep neural networks L Sundaram, H Gao, SR Padigepati, JF McRae, Y Li, JA Kosmicki, ... Nature genetics 50 (8), 1161-1170, 2018 | 547 | 2018 |
| RaptorX: exploiting structure information for protein alignment by statistical inference J Peng, J Xu Proteins: Structure, Function, and Bioinformatics 79 (S10), 161-171, 2011 | 477 | 2011 |
| Distance-based protein folding powered by deep learning J Xu Proceedings of the National Academy of Sciences 116 (34), 16856-16865, 2019 | 456 | 2019 |
| Predicting protein–protein interactions through sequence-based deep learning S Hashemifar, B Neyshabur, AA Khan, J Xu Bioinformatics 34 (17), i802-i810, 2018 | 434 | 2018 |
| Pairwise global alignment of protein interaction networks by matching neighborhood topology R Singh, J Xu, B Berger Annual International Conference on Research in Computational Molecular …, 2007 | 416 | 2007 |
| RAPTOR: optimal protein threading by linear programming J Xu, M Li, D Kim, Y Xu Journal of Bioinformatics and Computational Biology 1 (01), 95-117, 2003 | 371 | 2003 |
| Critical assessment of protein intrinsic disorder prediction M Necci, D Piovesan, CPJ Xu), DP Curators, SCE Tosatto Nature Methods, 2021 | 349 | 2021 |
| RaptorX server: a resource for template-based protein structure modeling M Källberg, G Margaryan, S Wang, J Ma, J Xu Protein Structure Prediction, 17-27, 2014 | 333 | 2014 |
| Identification of let-7–regulated oncofetal genes B Boyerinas, SM Park, N Shomron, MM Hedegaard, J Vinther, ... Cancer research 68 (8), 2587, 2008 | 297 | 2008 |
| Improved protein structure prediction by deep learning irrespective of co-evolution information J Xu, M Mcpartlon, J Li Nature Machine Intelligence, 2021 | 272 | 2021 |
| Conditional neural fields J Peng, L Bo, J Xu Advances in neural information processing systems 22, 1419-1427, 2009 | 232 | 2009 |
| Protein structure alignment beyond spatial proximity S Wang, J Ma, J Peng, J Xu Scientific reports 3, 1448, 2013 | 231 | 2013 |
| Protein threading using context-specific alignment potential J Ma, S Wang, F Zhao, J Xu Bioinformatics 29 (13), i257-i265, 2013 | 187 | 2013 |
Sheng WangZelixir BiotechVerified email at zelixir.com
