Zhang Lab

Led by Jie Zhang, PhD, the Zhang Lab focuses on the development and application of translational bioinformatics methods to identify disease genes, pathways and biomarkers in the areas of cancer, neurological disease, and other disorders.

The primary area of research for this lab includes biological data analysis using a variety of bioinformatics and systems biology tools. The major interests are applying network mining approach to study disease pathology and etiology, as well as identifying disease biomarker and stratifying patients. In addition, Next Generation Sequencing (NGS) data analysis and integration of multi-omics data for the study of the noted diseases is another research focus.

Research Updates

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The Zhang Lab provides an interdisciplinary teamwork-based research environment. Any student and/or postdoc from the fields of bioinformatics, computer science, electrical engineering and statistics background with an interest in applying their knowledge to solve biological problems and human diseases is welcomed to join the team.

Current Research Funding

ACS Internal Research Grant
Human Frontier Science Program
NCI ITCR U01 Grant

Recent Publications

S. Xiang, Z. Huang, Z. Han, C. Yu, H. Wang, 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, in press.

Y. Han, X. Ye, C. Wang, Y. Liu, W. Feng, K. Huang, and J. Zhang, “Integration of Molecular Features with Clinical Information for Predicting Outcome for Neuroblastoma Patients”, Biology Direct, 2018, in press.

Z. Han, T. Johnson, J. Zhang, K. Huang, “Functional Virtual Flow Cytometry – A Visual Analytic Approach for Characterizing Single Cell Gene Expression Patterns”, Biomed International, 2017, accepted.

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

J. Zhang, 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.

Research Team

Postdoc: Shunian Xiang, PhD
Co-supervised by Jun Cheng, PhD, and Kun Huang, PhD