| Evaluating dynamic bivariate correlations in resting-state fMRI: A comparison study and a new approach MA Lindquist, Y Xu, MB Nebel, BS Caffo Neuroimage 101, 531-546, 2014 | 425 | 2014 |
| Demystifying Multitask Deep Neural Networks for Quantitative Structure–Activity Relationships Y Xu, J Ma, A Liaw, RP Sheridan, V Svetnik Journal of Chemical Information and Modeling 57 (10), 2490-2504, 2017 | 260 | 2017 |
| Deep dive into machine learning models for protein engineering Y Xu, D Verma, RP Sheridan, A Liaw, J Ma, NM Marshall, J McIntosh, ... Journal of chemical information and modeling 60 (6), 2773-2790, 2020 | 249 | 2020 |
| Comparing test-retest reliability of dynamic functional connectivity methods AS Choe, MB Nebel, AD Barber, JR Cohen, Y Xu, JJ Pekar, B Caffo, ... NeuroImage 158, 155-175, 2017 | 221 | 2017 |
| Dynamics inside the cancer cell attractor reveal cell heterogeneity, limits of stability, and escape Q Li, A Wennborg, E Aurell, E Dekel, JZ Zou, Y Xu, S Huang, I Ernberg Proceedings of the National Academy of Sciences 113 (10), 2672-2677, 2016 | 138 | 2016 |
| Dynamic connectivity detection: an algorithm for determining functional connectivity change points in fMRI data Y Xu, MA Lindquist Frontiers in neuroscience 9, 285, 2015 | 106 | 2015 |
| Deep Neural Networks for QSAR Y Xu Artificial Intelligence in Drug Design, Methods in Molecular Biology 2390 …, 2021 | 69* | 2021 |
| Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure–Activity Relationship Models? RP Sheridan, P Karnachi, M Tudor, Y Xu, A Liaw, F Shah, AC Cheng, ... Journal of Chemical Information and Modeling 60 (4), 1969-1982, 2020 | 63 | 2020 |
| A mass spectrometry-based proteome map of drug action in lung cancer cell lines B Ruprecht, J Di Bernardo, Z Wang, X Mo, O Ursu, M Christopher, ... Nature Chemical Biology 16 (10), 1111-1119, 2020 | 57 | 2020 |
| Big data and neuroimaging Y Webb-Vargas, S Chen, A Fisher, A Mejia, Y Xu, C Crainiceanu, B Caffo, ... Statistics in biosciences 9, 543-558, 2017 | 17 | 2017 |
| Development and Evaluation of Conformal Prediction Methods for Quantitative Structure–Activity Relationship Y Xu, A Liaw, RP Sheridan, V Svetnik ACS Omega, 2024 | 12 | 2024 |
| A deep learning approach for automated sleep-wake scoring in pre-clinical animal models V Svetnik, TC Wang, Y Xu, BJ Hansen, SV Fox Journal of neuroscience methods 337, 108668, 2020 | 12 | 2020 |
| An M-estimator for reduced-rank system identification S Chen, K Liu, Y Yang, Y Xu, S Lee, M Lindquist, BS Caffo, JT Vogelstein Pattern Recognition Letters 86, 76-81, 2017 | 10* | 2017 |
| The N-leap method for stochastic simulation of coupled chemical reactions Y Xu, Y Lan The Journal of Chemical Physics 137 (20), 2012 | 8 | 2012 |
| High-Throughput Algorithmic Optimization of In Vitro Transcription for SARS-CoV-2 mRNA Vaccine Production SE McMinn, DV Miller, D Yur, K Stone, Y Xu, A Vikram, S Murali, ... Biochemistry, 2024 | 5 | 2024 |
| Dynamic sampling in autonomous process optimization M Christensen, Y Xu, EE Kwan, MJ Di Maso, Y Ji, M Reibarkh, AC Sun, ... Chemical Science 15 (19), 7160-7169, 2024 | 5 | 2024 |
| A Novel Machine Learning Based Framework for Developing Composite Digital Biomarkers of Disease Progression S Zhai, A Liaw, J Shen, Y Xu, V Svetnik, JJ FitzGerald, CA Antoniades, ... Frontiers in Digital Health, 2024 | 1 | 2024 |
| 0432 A Deep Learning Approach for Automated Sleep-Wake Scoring in Pre-Clinical Animal Models V Svetnik, T Wang, Y Xu, BJ Hansen, SV Fox Sleep 43, A166, 2020 | | 2020 |
Martin LindquistProfessor of Biostatistics, Johns Hopkins UniversityVerified email at jhsph.edu
