38859-Zhang, Jie
Faculty

Jie Zhang, PhD

Assistant Professor of Medical & Molecular Genetics

Address
HITS 5015
410 W. 10th, Ave,

Indianapolis, IN 46202
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Bio

B.S. in Biological Sciences and Biotechnology,  Tshinghua University, China

Ph.D. in Biochemistry, University of Illinois, Urbana-Champaign, IL

Postdoc in Bioinformatics, The Ohio State University, Columbus, OH

Key Publications

  1. 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, and 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, accepted

2. 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 author)

3. 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, Jul 15; PP |doi: 10.1109/TMI.2021.3097319.

4. 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”, Nature Communications, 12, 3445 (2021) |doi:10.1038/s41467-021-23774.w

5. 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”, Scientific Reports, 2021 Jan. 11;11:353 |doi: 0.1038/s41598-020-79740-x.

6.  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 translocation renal cell carcinoma”, Nature Communications, (2020) 11:1778, doi: 10.1038/s41467-020-15671-5.

7.  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, Y. Yang, “Attenuation of SMARCA4 and ERK-ETS signaling suppress dopaminergic degeneration in Drosophila Parkinson’s disease models”, Aging Cell, (2020) doi:10.1111/acel.13210 (*co-first author). 

8. Z, Huang, T. Johnson, Z. Han, B.R. Helm, S. Cao, C. Zhang, P. Salama, M. Rizkalla, C. Y. Yu, J. Cheng, S. Xiang, X. Zhan, J. Zhang, K. Huang, “Deep Learning-based Cancer Survival Prognosis from RNA-seq Data: Approaches and Evaluations”, BMC Medical Genomics, 13, 41 (2020), doi:10.1186/s12920-020-0686-1.

9.  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. (*co-corresponding authors).

10. T. S. Johnson, T. Wang, Z. Huang, C. Y. Yu, Y. Wu, Y. Han, Y. Zhang, K. Huang, and J. Zhang, “LAmbDA: Label Ambiguous Domain Adaptation Dataset Integration Reduces Batch Effects and Improves Subtype Detection”, Bioinformatics, Apr. 30, 2019, doi: 10.1093/bioinformatics/btz295

11. S. Xiang, Z. Huang, H. Wang, Z. Han, C. Y. Yu, D. Ni, K. Huang, and J. Zhang, “Condition-specific Gene Co-expression Network Mining Identified Key Pathways and Regulators in Alzheimer’s Disease”, BMC Medical Genomics, 2018 Dec 31;11(Suppl 6):115. doi: 10.1186/s12920-018-0431-1.

12.  J. Chen*, J. Zhang*, Y. Han, X. Wang, X. Ye, Y. Meng, A. Pawani, Z. Han, Q. Feng, and K. Huang, “Integrative analysis of histopathological images and genomic data for predicting clear cell renal cell carcinoma prognosis”, Cancer Research, 2017 Nov; 77(21): e91-e100. (*co-first authors)

13. J. Zhang, and K. Huang, “Pan-cancer analysis of frequent DNA co-methylation patterns reveals consistent epigenetic landscape changes in multiple cancers”, BMC Genomics, 2017 Jan 25;18(Suppl 1):1045. doi: 10.1186/s12864-016-3259-0.

14.   J. Zhang, and K. Huang, “Normalized lmQCM: An Algorithm for Detecting Weak Quasi-Cliques in Weighted Graph with Applications in Gene Co-Expression Module Discovery in Cancers”. Cancer Inform. 2016 Jul 24;13(Suppl 3):137-46.

15. S. Shroff*, J. Zhang*, and K. Huang, “Gene Co-Expression Analysis Predicts Genetic Variants Associated with Drug Responsiveness in Lung Cancer”, AMIA Joint Summits Transl Sci Proc. 2016 Jul 20; 2016: 32-41. (*equal contributions, Winner of the Marco Ramoni Distinguished Paper award)

16.   T. Bailey, P. Krajewski, I. Ladunga, C. Lefebvre, Q. Li, T. Liu, P. Madrigal, C. Taslim, and J. Zhang, Practical Guidelines for the Comprehensive Analysis of ChIP-seq data”, PloS Comp. Biol. Nov 14, 2013, 9(11): e1003326, DOI: 10.1371/journal.pcbi.1003326

17. Y. Xiang, J. Zhang, and K. Huang, "Mining tissue-tissue gene co-expression network for tumor microenvironment study and biomarker prediction", BMC Genomics, 14(S5): S4, 2013.

18. J. Zhang, K. Lu, Y. Xiang, M. Islam, S. Kotian, Z. Kais, C. Lee, M. Arora, H. Liu, J. D. Parvin, and K. Huang, “Weighted Frequent Gene Co-expression Network Mining to Identify Genes Involved in Genome Stability”, PLoS Comput. Biol. 8(8): e1002656. doi:10.1371 /journal.pcbi.1002656, 2012.

 

Titles & Appointments

  • Assistant Professor of Medical & Molecular Genetics
  • Adjunct Assistant Professor of Biostatistics & Health Data Science
  • Adjunct Assistant Professor, School of Informatics & Computing
  • Assistant Professor in Center for Computational Biology and Bioinformatics
  • Education
    2002 PhD University of Illinois
    1996 BS Tsinghua University
  • Research

    Our lab is focused on developing and applying translational bioinformatics and system biology methods to identify disease genes, pathways, and biomarkers with applications in cancers, neurological diseases, and other types of diseases.

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