Dr. Fengzhu Sun

About Dr. Fengzhu Sun

Dr. Fengzhu Sun is a Professor of Quantitative and Computational Biology and Mathematics. His Bachelors in Mathematics is from Shandong University, Masters in Probability and Statistics is from Peking University, and PhD in Applied Mathematics is from University of Southern California. He came back to USC in 2000 as an associate professor after being an assistant professor of genetics and biostatistics at Emory University from 1995 to 2000. He has been a professor since 2006.

Professor Sun works in the area of Computational Biology and Bioinformatics, Statistical Genetics, and Mathematical Modeling. His research interests include protein interaction networks, gene expression, single nucleotide polymorphisms (SNP), linkage disequilibrium (LD) and their applications in predicting protein functions, gene regulation networks, and disease gene identification. His recent research interests include alignment-free genome and metagenome comparison and metagenomics.

His previous research accomplishments include: 1) virus and virus-host interaction in metagenomes, 2) new alignment-free statistics including d2* and d2s for genome and metagenome comparison, 3) a suite of algorithms for local similarity analysis (LSA) of time series data, 4) protein domain interaction and protein function prediction integrating multiple data sources, 5) dynamic programming algorithms for haplotype block partition and tag SNP selection, 6) 1-TDT: transmission disequilibrium test when one parent is available, and 7) theoretical studies of polymerase chain reaction (PCR) related biotechnologies.

Professor Sun is an elected fellow of the American Association for the Advancement of Sciences (AAAS, 2012), American Statistical Association (ASA, 2015), and Institute of Mathematical Statistics (IMS, 2023). He is also an elected member of the International Statistical Institute (ISI, 2012), and a recipient of USC Mellon Mentoring award for faculty mentoring (2012). In 2017, he received the USC Dornsife College senior Raubenheimer Outstanding Faculty Award for excellence in the areas of research, teaching and service.

Research Statement

Research interests: Metagenomics, Statistical Genetics, Mathematical Modeling, and Computational Biology.

The primary objective is to develop mathematical, statistical, and computational tools to solve biological problems.

My current research interests are on metagenomics and molecular sequence analysis. We collaborate with molecular ecologists and clinicians on investigating the microbial organisms and their abundance levels in microbial communities and their impact on community function and public health. We also develop computational methods for studying relationships among molecular sequences and microbial communities.

Previously, we developed mathematical and statistical tools to locate genetic mutations responsible for complex diseases or traits, and to understand molecular functions combining different information such as protein-protein interactions, gene expression and regulatory elements.

Our major accomplishments include: 1) identification of bacteriophages and phage-host interactions in metagenomes, 2) alignment-free genome and metagenome comparison using d2* and d2s, 3) association networks in microbial communities using local similarity analysis (LSA), 4) dynamic programming algorithms for haplotype block partition and tagSNP selection and their applications to association studies, 5) integrated approaches for protein function prediction, domain interaction prediction and pathway inference, and 6) integrated approaches for disease gene identification.