Jin Zhang, PhD, focuses on creating and integrating advanced computational approaches using high-throughput sequencing data and imaging data into the development of novel diagnostic, prognostic, and therapeutic strategies in cancer. The lab has developed a series of gene fusion discovery and gene fusion function predicting tools, and discovered novel gene fusion biomarkers in endocrine therapy resistant breast carcinoma, mixed fibrolamellar hepatocellular carcinoma, and relapsed adult B lymphoblastic leukemia. Besides gene fusions, they have also characterized the landscape of small RNAs (17-200nt) and long non-coding RNAs (>200nt) using novel deep sequencing technologies in acute myeloid leukemia and prostate adenocarcinoma. The Zhang Lab is currently collaborating with Radiation Oncologists, Physicists, and Molecular Biologists to elucidate the cancer biology and discover novel biomarkers of cervical squamous cell carcinoma and endocervical adenocarcinoma, through studying the interaction of human papillomavirus (HPV) and cervical cancer gene expression, the alteration of small RNA expression in cervical cancer, and the alterations of pathways that influence cervical cancer glucose metabolism and the response to radiation and chemotherapy.
Dr. Zhang’s lab has also been developing novel informatics approaches to address the critical need for analyzing the rapidly expanding quantities of biological and medical data to impact patient care, including advanced algorithms in split read alignment, pan-cancer analysis using cloud computing, and machine learning techniques. His article of the state-of-the-art gene fusion discovery tool (INTEGRATE) he developed was featured in the 2017 International Medical Informatics Association Yearbook, as one of the four best articles in the ‘Bioinformatics and Translational Informatics’ subfield of medical informatics literature published in the year 2016.
For more information about research opportunities in this laboratory, please contact Dr. Jin Zhang (email@example.com).