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.
Shufen received her M.Sc. degree from the Southern Medical University and is pursuing her Ph.D. at Fudan University. She utilizes genetics-led approaches to decipher cardiovascular diseases, including genetic correlations, immune factors and drug targets. She is enthusiastic about integrating large public datasets and developing novel algorithms. She is skilled in statistical analysis (R and SAS), programming languages (R, Python, perl) and Linux operating environment. Shufen joined the Pan Lab in July 2022.
Min received her M.Sc. degree from the South China University of Technology (SCUT) and is pursuing her Ph.D. at the School of Medicine, SCUT. Her research applies high-throughput omics technologies and computation, including DNA methylation, metabolomics and genomics, to studying the development and prognosis of coronary artery disease. Min joined the Pan Lab in March 2022.
Zhuoyi received her B.Sc. degree from Guangzhou Medical University and is currently pursuing a M.Sc. in Clinical Pharmacy at Southern Medical University. She is interested in multi-omics data analysis and computer-aided drug design for cardiovascular diseases. Zhuoyi joined the Pan Lab in May 2023.
Zhiyan received her Ph.D degree in Biomedical Science from Macau University and M.Sc. degree in pharmaceutic analysis from Sichuan University. Her research focuses on analyzing multidimensional data of immune-related diseases, including metabolomics, microbiome and proteomics, to assess the relationship among host, microbes, disease and efficacy of therapies. She is proficient in operating high-resolution mass spectrometer and develops optimal analytical methods for multiple biological matrixes, and skilled in data analysis using R language and omics data processing software. She publishes in metabolomics, microbiome, Chinese medicines and mass spectrum in SCI journals. Zhiyan joined the Pan Lab in January 2024.
Hanshuo received her Ph.D. degree in Microbiology from University of Liverpool and M.Sc. degree in Infection and Immunity from University of College London. Her research applies deep learning algorithms on omics big data to decode immune responses in cardiovascular diseases. Hanshuo joined the Pan Lab in February 2024.
Yonglin earned his M.Sc. degree from Southern Medical University (SMU). His research integrates multiomics data to explore and understand the complex regulatory mechanisms behind non-coding SNPs. Yonglin joined the Pan Lab in July 2023.
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.
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 focused on molecular evolution and genome biodiversity and 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.
