| Classification of whole mammogram and tomosynthesis images using deep convolutional neural networks X Zhang, Y Zhang, EY Han, N Jacobs, Q Han, X Wang, J Liu IEEE transactions on nanobioscience 17 (3), 237-242, 2018 | 124 | 2018 |
| Exosomal lipids for classifying early and late stage non-small cell lung cancer TWM Fan, X Zhang, C Wang, Y Yang, WY Kang, S Arnold, RM Higashi, ... Analytica chimica acta 1037, 256-264, 2018 | 80 | 2018 |
| Whole mammogram image classification with convolutional neural networks X Zhang, Y Zhang, EY Han, N Jacobs, Q Han, X Wang, J Liu 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2017 | 56 | 2017 |
| Incorporating protein dynamics through ensemble docking in machine learning models to predict drug binding F Alghamedy, J Bopaiah, D Jones, X Zhang, HL Weiss, SR Ellingson AMIA Summits on Translational Science Proceedings 2018, 26, 2018 | 12 | 2018 |
| TFmeta: A Machine Learning Approach to Uncover Transcription Factors Governing Metabolic Reprogramming Y Zhang, X Zhang, AN Lane, TWM Fan, J Liu Proceedings of the 2018 ACM International Conference on Bioinformatics …, 2018 | 4 | 2018 |
| Towards a better understanding of on and off target effects of the lymphocyte-specific kinase lck for the development of novel and safer pharmaceuticals X Zhang, A Kucharski, WA de Jong Procedia Computer Science 108, 1222-1231, 2017 | 2 | 2017 |
| Computationally characterizing genomic pipelines using high-confident call sets X Zhang, SR Ellingson Procedia Computer Science 80, 1023-1032, 2016 | 2 | 2016 |
| Computationally characterizing genomic pipelines and benchmarking results using GATK best practices on the high performance computing cluster at the University of Kentucky X Zhang, SR Ellingson BMC BIOINFORMATICS 17, 2016 | | 2016 |
