Immunome Research
Open Access

Guanglan Zhang

Biography

I am an Assistant Professor, the faculty coordinator of the Health Informatics Program, and the director of health informatics research lab at Computer Science Department, Metropolitan College (MET) at Boston University. I am also an adjunct member of Bioinformatics Core at Cancer Vaccine Center (CVC), Dana-Farber Cancer Institute (DFCI) and Harvard Medical School. During the 15 years of pursuing research in biomedical and health sciences, I have authored more than 30 journal publications and developed more than a dozen online computational systems. I am the co-inventor of two patents demonstrating the originality of the work. Through the development of advanced computational solutions, I contribute to the rapid progress of basic and applied biology and biomedicine. Besides research work, I have been actively contributing to the research community by organizing conference workshops, competitions, and joining workshop program committees. I regularly review papers for more than ten biomedical and bioinformatics journals, including some high-impact journals such as Briefings in Bioinformatics and Nucleic Acid Research. I am also the review editor of Frontiers in T Cell Biology. My research focus has been in immunoinformatics, specifically on the development of computational algorithms in immunological sciences. My major research interests include computational modeling of complex biological processes, such as the identification of vaccine targets, the development of KB-builder - a framework for rapid development of next-generation biological databases, the building of analytical tools for pattern recognition from biomedical data, and the design of diagnostic tools. KB-builder provides a semi-automatic approach for collecting, cleaning, and organizing data, integration of advanced analytical tools and workflows for in-depth analysis of various structural and functional properties associated with immune responses and vaccine development. It speeds up the biological research and vaccine design by providing specialist databases hosting cleaned, well-annotated and structured data and integrating them into data mining pipeline for the discovery of new knowledge. It has been deployed in multiple projects (HLA typing, Epstein-Barr virus, Merkel cell polyomavirus, influenza A virus, flavivirus, human papilloma virus, and tumor T-cell antigens). The framework is modularized and can be rapidly deployed to any project that involves biological data storage, retrieval, annotation, and analysis.

Research Interest

Immunoinformatics, computational modeling