We are a team of scientists dedicated to decoding complex human diseases by means of intelligent computing on biomedical data. Specifically, we leverage omics measurements, such as genome, epigenome, proteome, metabolome and other types of data, combined with advanced computing methods and domain knowledge, for understanding what predisposes an individual to a certain disease, what goes wrong at the diseased states, and what are the biomarkers that broadly represent the malfunctioned physiology. In addition, we develop mathematical models that predict disease risks and development trajectories. We collaborate extensively on population genetics, cardiovascular diseases and immunology.
Director of Bioinformatics (2014-2021), VA Palo Alto, USA
Postdoc (2010-2013), Stanford University, USA.
Ph.D. (2008), Max-Planck Institute for Biochemistry, Germany
Dr. Pan has extensive experience in omics technologies and computational strategies to decode cardiometablic diseases, including mapping the critical signal transduction pathways, identifying the signature biomolecules, inferring potential drug targets and effects, and constructing disease risk prediction models. She also pioneered cloud computing technologies for big data genomics and applied them to the whole genome sequencing initiatives in the US Million Veteran Program. She publishes on cardiometabolic diseases, population genetics, and big data computing.
Min received her Master of Science degree from the South China University of Technology (SCUT). Currently she is pursuing her Ph.D. at the School of Medicine, SCUT. Her research focuses on applying high-throughput multiomics technologies, including DNA methylation, metabolomics and genomics, to studying the development and prognosis of coronary artery disease. Min joined the Pan Lab in March 2022.
Shufen received her MS degree from the Southern Medical University. She is pursuing her Ph.D. at Fudan University. Her research directions are the analysis of multi-omics data of cardiovascular diseases and the development of algorithm. Her research skills are mainly in statistical analysis (R and SAS), programming languages (R, Python, perl) and she is familiar with Linux operating environment. Shufen joined the Pan Lab in July 2022.
Hadi was born in Mazandaran Province (Iran) 1986, and graduated from Kunming College of Life Science, University of Chinese Academy of Sciences (CAS) with a Doctor of Philosophy in Genetics in 2019. As a Ph.D. student in CAS, he has been focusing his research on molecular evolution and genome biodiversity. In both his Ph.D. and honours research, he utilized multiple DNA analysis techniques including both whole exome and whole genome sequencing. He was awarded the CAS-TWAS president fellowship for Ph.D., from CAS and The World Academy of Sciences (TWAS) and received recognition for excellent contribution to student activities at the International College of CAS. Hadi published several papers in SCI journals such as Human Genomics, BMC Evolutionary Biology, Molecular Biology Evolution, and Zoological Research. In April 2022, he joined the Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, as a postdoctoral scholar for biomedical intelligent computing.
Guoqiang's research interests include transcriptomic analysis, gene mutation analysis and identifying gene family structure. He also has experience in developing high-throughput sequencing products including microbial metagenomics and tumor mutation detection.
Data science enthusiast. Experienced Research Assistant with a demonstrated history of working in biostatistics. Solid background in statistics. Master of Science degree in Hong Kong Baptist University, focused on Data Mining. His projects utilized single-cell transcriptomics, proteomics and multiomics integration, among various other data science techniques, to study immune and metabolic diseases. Yuanbang worked in the Pan Lab from February to August 2022, then left to start his Ph.D. study in Fudan University.
