Dr. Zhang is a computational biologist and bioinformatician whose research interests include: developing genetics and bioinformatics methods that can be applied to advance the understanding of the complex neural processing associated with disorders disease and cancer diseases and to enhance clinical applications of imaging and genomics by assisting in diagnostic, prognostic, and therapeutic assessments.
Dr. Zhang obtained a Ph.D in Computer Science and had postdoc training in Biostatistics and Bioinformatics and Neurology depts., separately, before he was appointed as Assistant and Associate Professor in the Institute for Personalized Medicine, the Dept of Biochemistry and Molecular Biology, the Cancer Institute at the Penn State University (PSU). Dr. Zhang joined CWRU in 2022 and continued his research on computational and statistical methodology and analysis on high-dimensional biomedical data.
Dr. Zhang has ample experience in genetic analyses and computer science with comprehensive training in data mining on large databases, efficient parallel computation, and software package development. He has extensive collaboration with computer scientists, clinicians, and biologists on different biomedical fields, including neuroimaging analysis, WGS/WES mutation/structural variation analysis, virus/bacterial assembly, pathogen analysis, and RNA analysis in Parkinsons, Alzheimer, Bipolar, Head/Neck Cancer, AML, and Neonatal Sepsis diseases.
My research focuses on developing bioinformatics and statistical methods to identify biomarkers and mechanisms underlying different human diseases and cancers.
Cancer Research: This research focuses on developing genome-wide integrated framework for genome analysis to identify novel genetic alterations in cancer cell lines and the resulting effect on gene expression using next generation sequencing data (WGS, WES, RNA, HiC, MinION, OGM).
Neuroimaging Research: This research focuses on three computational and statistical frameworks to solve challenging problems rising in biomedical analysis: (i) to analyze localized brain neural activity and connectivity network using fMRI big data, (ii) to classify and predict disease progression and therapeutic treatment response based on longitudinal neuroimaging data using Bayesian hierarchical model, (iii) to investigate biomarkers and information fusion by combining multi-modalities data sources, such as fMRI, DTI, PET, T1/T2, genomic and clinical information
Microbial Research: This research focuses on pathogen detection and microorganism identification with sequencing technologies (RNA, 16srRNA, MinION)
Awards and Honors
Adjunct Professor Pennsylvania State University
Graduate trainer Systems Biology and Bioinformatics, CWRU