Jie Zhang, PhD

Key Publications

T. Wang, T. S. Johnson, W. Shao, Z. Lu, B. R. Helm, J. Zhang, and K. Huang, “BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes”, Genome Biology, (2019) 20:165. |doi: 10.1186/s13059-019-1764-6. 

W. Shao, S. Xiang, Z. Zhang, K. Huang, J. Zhang†, “Hyper-graph Based Sparse Canonical Correlation Analysis for The Diagnosis of Alzheimer’s Disease from Multi-dimensional Genomic Data”, Methods, 2020 Apr 28; S1046-2023(20)30021-9 |doi: 10.1016/j.ymeth.2020.04.008. 

J. Cheng, Z. Han, R. Mehra, W. Shao, M. Cheng, Q. Feng, D. Ni, K. Huang, L. Cheng, and J. Zhang, “Computational Analysis of Pathological Images Enables A Better Diagnosis of TFE3 Xp11.2 Translocation Renal Cell Carcinoma”, Nature Communications, (2020)11:1778 |doi:10.1038/s41467-020-15671-5. 

L. Sun*, J. Zhang*, W. Chen*, Y. Chen, X. Zhang, M. Yang, M. Xiao, F. Ma, Y. Yao, M. Ye, Z. Zhang, K. Chen, F. Chen, Y. Ren, S. Ni, Xi Zhang, Z. Yan, Z. Sun, H. Zhou, H. Yang, S. Xie, M E. Haque, K. Huang, and Y. Yang, “Attenuation of SMARCA4 and ERK-ETS Signaling Suppress Dopaminergic Degeneration in Drosophila Parkinson’s Disease Models”, Aging Cell, 2020;19:e13210 |doi: 10.1111/acel.13210. (*co-first authors)

W. Shao, T. Wang, L. Sun, T. Dong, Z. Han, Z. Huang, J. Zhang†, D. Zhang, and K. Huang, “Multi-task Multi-modal Learning for Joint Diagnosis and Prognosis of Human Cancers”, Med. Imaging Analysis, 2020 Oct; 65:101795 |doi: 10.1016/j.media.2020.101795. 

T. S. Johnson, S. Xiang, B. R. Helms, Z. B. Abrams, P. Neidecker, R. Machiraju, Y. Zhang, K. Huang, and J. Zhang, “Spatial Cell Type Composition in Human Normal and Alzheimer Brains is Revealed Using Integrated Mouse and Human Single Cell RNA Sequencing”, Sci. Rep., 2020 Oct. 22; 10(1), 18014 |doi:10.1038/s41598-020-74917-w. 

T. S. Johnson, S. Xiang, T. Dong, M. Cheng, T. Wang, K. Yang, D. Ni, K. Huang, J. Zhang, “Combined Differential Expression and Differential Co-expression Analysis on Gene Networks Reveals Changes in Cell Population Largely Explain Core Microglia Genes’ Up-expression in Alzheimer’s Disease Brains”, Sci. Rep., 2021 Jan. 11;11:353 |doi: 10.1038/s41598-020-79740-x. 

T. Wang, W. Shao, Z. Huang, H. Tang, J. Zhang, Z. Ding, K. Huang, “MOGONET Integrates Multi-omics Data Using Graph Convolutional Networks Allowing Patient Classification and Biomarker Identification”, Nat. Comm., 12, 3445 (2021) |doi:10.1038/s41467-021-23774.w 

W. Shao, T. Wang, Z. Huang, Z. Han, J. Zhang, K. Huang, “Weakly Supervised Deep Ordinal Cox Model for Survival Prediction from Whole-slide Pathological Images”, IEEE Transaction on Medical Imaging, 2021, IEEE Trans Med Imaging, 2021 Jul 15;PP |doi: 10.1109/TMI.2021.3097319. 

X. Huang, K. Huang, T. Johnson, M. Radovich, J. Zhang*, J. Ma*, Y. Wang* “ParsVNN: Parsimony Visible Neural Networks for Uncovering Cancer-Specific and Drug-sensitive Genes and Pathways”, Nucl. Acid Res. in Genomics and Bioinformatics, Vol.3, Issue 4, Dec. 2021, lqab097 |doi.org/10.1093/nargab/lqab097. (*co-corresponding authors)

Z. Liu, T. Johnson, W. Shao, M. Zhang, J. Zhang, K. Huang, “Optimal transport- and kernel-based early detection of mild cognitive impairment patients based on magnetic resonance and positron emission tomography images”, Alzheimer’s Res Ther. 2022; 14: 4. Jan, 2022 |doi: 10.1186/s13195-021-00915-3. 

T. S. Johnson, C. Y. Yu, Z. Huang, S. Xu, T. Wang, C. Dong, W. Shao, M. A. Zaid, Y. Wang, C. Bartlett, Y. Zhang, Y. Liu K. Huang, J. Zhang, “Diagnostic Evidence GAuge of Single cells (DEGAS): A transfer learning framework to infer impressions of cellular and patient phenotypes between patients and single cells”, Genome Medicine, 14, 11 (2022) |doi.org/10.1186/s13073-022-01012-2. 

Y. Liu, T. Wang, B. Duggan, M. Sharpnack, K. Huang, J. Zhang, X. Ye, T. S. Johnson, “SPCS: A Spatial and Pattern Combined Smoothing Method for Spatial Transcriptomic Expression”, Brief Bioinfor. 2022 Apr 4; bbac116. |doi: 10.1093/bib/bbac116. 

Z. Huang, W. Shao, Z. Han, A. M. Alkashash, C. De la Sancha, A. V. Parwani, H. Nitta, Y. Hou8, T. Wang, P. Salama, M. Rizkalla, J. Zhang, K. Huang, Z. Li, “Artificial Intelligence Reveals Features Associate with Breast Cancer Neoadjuvant Chemotherapy Response from Multi-stain Histopathologic Images”, NPJ Precision Oncology, 7, 14 (2023) |doi:10.1038/s41698-023-00352-5. 

P. H. Pandya, A. J. Jannu, et al…, J. Zhang*, K. E. Pollok*, “Integrative Multi-OMICs Identifies Therapeutic Response Biomarkers and Confirms Fidelity of Clinically Annotated, Serially Passaged Patient-Derived Xenografts Established from Primary and Metastatic Pediatric and AYA Solid Tumors”, Cancers, 2023, 15(1), 259 |doi.org/10.3390/cancers15010259.  (*co-corresponding authors)

J. E. Couetil, Z. Liu, K. Huang, J. Zhang*, A. Alomari*, “Predicting melanoma survival and metastasis with interpretable histopathological features of machine learning models”, Front.  Med., Volume 9, 2022 | doi:10.3389/fmed.2022.1029227.  (*co-corresponding authors)

X. Zhan, Y. Liu, A. J. Jannu, S. Huang, W. Wei, B. Ye, P. Pandya, K. Pollok, J. Renbarger, K. Huang, J. Zhang, “Identify the potential driver genes for gene fusion-negative rhabdomyosarcoma”, Front. Onc., Volume 13, 2023 | doi:10.3389/fonc.2023.1080989.