Yanding Zhao
Assistant Professor of Computational Biology
Research Interests
Professor Zhao's teaching and research interests span the development of AI-driven frameworks to decode tumor evolution, complex genome architecture, and multi-omics regulation. His work seeks to uncover the fundamental principles governing cancer biology by integrating high-resolution genomic data with advanced machine learning. By characterizing the interplay between structural variations and the tumor microenvironment, his research aims to translate these biological laws into precise therapeutic strategies.
Email
Prior to joining MBZUAI, Professor Zhao completed his postdoctoral training at Stanford University, where he was co-mentored by Dr. Howard Y. Chang and Dr. Christina Curtis. His work there focused on linking genetic alterations to 3D genome architecture, particularly through the lens of extrachromosomal DNA (ecDNA). This research led to a seminal publication in Nature Genetics (2024), where he developed computational frameworks to identify enhancer mutations and novel promoter-enhancer interactions on ecDNA resulting from structural rearrangements. He earned his Ph.D. in Computational Biology at Dartmouth College and Baylor College of Medicine under the mentorship of Dr. Chao Cheng, following his masterís training in biochemistry at Brandeis University with Dr. Jeff Gelles.
Looking ahead to the paradigm shift in cancer research driven by AI, Professor Zhao aims to bridge the gap between complex genomic data and fundamental biological laws. His research program at MBZUAI will concentrate on developing interpretable models to elucidate the functional consequences of structural variations (SVs), such as the RS3 signature, which he identified as a key driver of chromosomal instability and poor prognosis in osteosarcoma. Specifically, he plans to leverage high-resolution spatial transcriptomics and single-cell multi-omics to characterize the interplay between genomic architecture and the tumor immune microenvironment. These efforts seek to advance the quantitative understanding of how complex genomes evolve and to provide rational designs for next-generation precision oncology.
Looking ahead to the paradigm shift in cancer research driven by AI, Professor Zhao aims to bridge the gap between complex genomic data and fundamental biological laws. His research program at MBZUAI will concentrate on developing interpretable models to elucidate the functional consequences of structural variations (SVs), such as the RS3 signature, which he identified as a key driver of chromosomal instability and poor prognosis in osteosarcoma. Specifically, he plans to leverage high-resolution spatial transcriptomics and single-cell multi-omics to characterize the interplay between genomic architecture and the tumor immune microenvironment. These efforts seek to advance the quantitative understanding of how complex genomes evolve and to provide rational designs for next-generation precision oncology.
- Ph.D. in Genetics, Dartmouth College, USA
- M.Sc. in Molecular and Cell Biology, Brandeis University, USA
- B.Sc. in Biotechnology, Southern Medical University, USA
- Arima Genomics Open Grant, 2025
- MIB Agents FACTOR Travel Award, 2025
- PacBio-Stanford Genomics SMART Seed Grant, 2024
- Dartmouth Graduate Student Travel Awards, 2019
- Dartmouth College MCB student fellowship, 2015
- Brandeis University MCB student fellowship, 2014
- The Excellent Graduate Student of Southern Medical University, 2013
- The First Prize in Biochemistry Experiment Skills Contest of Guangdong, 2010
- Yost KE*, Zhao Y*, Hung KL, Zhu K, Xu D, Corces MR, et al.: "Three-dimensional genome landscape of primary human cancers", Nat Genet, 2025 May;57(5):1189-200.
- ElTanbouly MA*, Zhao Y*, Nowak E, Li J, Schaafsma E, Le Mercier I, et al.: "VISTA is a checkpoint regulator for naive T cell quiescence and peripheral tolerance", Science, 2020 Jan 17;367(6475):eaay0524.
- Wolf BK*, Zhao Y*, McCray A, Hawk WH, Deary LT, Sugiarto NW, et al.: "Cooperation of chromatin remodeling SWI/SNF complex and pioneer factor AP-1 shapes 3D enhancer landscapes", Nat Struct Mol Biol, 2023 Jan;30(1):10-21.
- Zhao Y, Schaafsma E, Gorlov IP, Hernando E, Thomas NE, Shen R, et al.: "A Leukocyte Infiltration Score Defined by a Gene Signature Predicts Melanoma Patient Prognosis", Mol Cancer Res. 2019 Jan;17(1):109-19.
- Zhao Y, Varn FS, Cai G, Xiao F, Amos CI, Cheng C.: "A P53-Deficiency Gene Signature Predicts Recurrence Risk of Patients with Early-Stage Lung Adenocarcinoma", Cancer Epidemiol Biomarkers Prev. 2018 Jan;27(1):86-95.