Hufeng Zhou
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Eductional and Training
More than a decade of experience and training in computational biology.
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Dr. Zhou is
a scientist and an engineer.
Dr. Hufeng Zhou is an Instructor (Junior Faculty Member) at Harvard Medical School and Research Scientist in Harvard T. H. Chan School of Public Health with more than 15 years of expertise in exploring fundamental epigenetic mechanisms of EBV-associated cancers using Next-Generation Sequencing technologies. He is world-renowned for his expertise in human genetics, particularly in rare variant association studies, functional annotation of human genetics variants, and quality control of super large scale of whole genome/exome sequencing studies.
Dr. Zhou's broad research interests also involves investigating the regulatory effects of EBV super-enhancers through non-coding RNA and long-range interactions, using 3D genomics and functional information to identify disease-related variants, and applying machine learning strategies to clinical data. Additionally, he has years of research experience in protein-protein interactions, pathway data integration and analysis, human-microbiome metagenomic data analysis, and software and database development.
Mt. Sinai Hospital
This picture was taken at the most special moment in my life, when I was presenting my work on the FAVOR functional annotation database at a conference at Mt. Sinai Hospital. After my presentation, I took a walk around the Central Park nearby, and that was the start of my whole new life. It was a moment of immense pride and satisfaction, having the opportunity to share my work and ideas with experts in the field. The experience was truly unforgettable and reinforced my passion for pursuing a career in this field.
Feb 2020.
Computational Biologist and Engineer
Dr. Zhou is a highly accomplished Computational Biologist and Engineer, well-versed in conducting cutting-edge scientific research in the field of human genomics. In addition to his research pursuits, Dr. Zhou has made notable contributions to advancing the study of human genomics through his development of various innovative tools and technologies. For instance, he has designed and implemented pathway databases such as IntPath, functional annotation databases like FAVOR, and novel algorithms for predicting host-pathogen interactions. Dr. Zhou has also developed tools to construct novel regulatory networks of transcriptome, further demonstrating his expertise in this field..
Passionate Trail Biker and Rower
Dr. Zhou is an accomplished mountain biker with a particular interest in cross-country trail biking and an avid rower. Despite engaging in intensive programming and research throughout the day, he finds solace in exploring cross-country trails in the nearby woods and reserves, as well as rowing down the Charles River from MIT to Harvard on sunny days. Engaging in these sports promotes both physical and mental well-being and keeps Dr. Zhou enthusiastic, energized, and level-headed in his competitive career.
Accomplished Scientist
Dr. Zhou is a distinguished scientist with over 15 years of dedicated and fruitful experience in the fields of computational biology and biostatistics, with a particular focus on human genetics. He has made significant contributions to the study of human population genetics, functional annotation of human genetic variants, epigenomics and chromatin confirmation, and proteomics of human and microbes. Dr. Zhou's research has been widely cited and has had a profound impact on the fields in which he works.
Global and Inclusive Mindset
Dr. Zhou's mission is to advance humanity through his research, focusing on better understanding human genetic diseases, drug targets for infectious diseases, and developing more sensitive and effective screening technologies. He lives by the motto, "To ordain conscience for Heaven and Earth. To secure life and fortune for the populace. To continue lost teachings for past sages. To establish peace for all future generations." (为天地立心，为生民立命，为往圣继绝学，为万世开太平。)
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Peer Reviewed Research Articles
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Dedicated Experience
Selected Work
FAVOR integrates variant functional information from multiple sources to describe the functional characteristics of variants and facilitates prioritizing plausible causal variants influencing human phenotypes. Furthermore, we provide a scalable annotation tool, FAVORannotator, to functionally annotate large-scale WGS studies and efficiently store the genotype and their variant functional annotation data in a single file using the annotated Genomic Data Structure (aGDS) format, making downstream analysis more convenient.
FAVOR / Nucleic Acids Research / 2023
We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce ‘annotation principal components’, multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits.
STAAR / Nature Genetics / 2020
Detecting rare-variant associations in the noncoding genome is challenging. We present a scalable, flexible and streamlined rare-variant association analysis framework for biobank-scale whole-genome sequencing data, including gene-centric and non-gene-centric analyses by incorporating multiple variant functional annotations using various coding and noncoding units, conditional analysis, result summary and visualization.
STAARpipeline / Nature Methods / 2023
