Selected Research Contributions
2022–2024
Initiated the study and brought together collaborators; developed the model and performed regulatory and structural interpretation. GET predicts expression across 213 human cell types and identified a transcription-factor interaction implicated in inherited leukemia risk. Co-first and co-corresponding author, Nature (2025).
2026
p53–ER regulation in breast cancer and chromatin changes in muscle aging
Developed Motiverse for GPU-accelerated motif-spacing analysis. Identified primate-specific Alu-derived p53–ER motif spacing of approximately 73 bp, supporting potential cooperation on the same nucleosome in breast cancer. Identified regulatory elements with age-associated accessibility changes in muscle cell types and tenocytes. Co-first and co-corresponding author; unpublished manuscript (2026).
Co-designed the data curation and quality-control pipeline, model architecture, training paradigm, and mechanistic interpretation analyses of the protein encoder. The study identified and experimentally validated regulators of T-cell exhaustion. Co-first author; bioRxiv (2025; revised 2026).
Additional Research Contributions
2021–2023
Used AlphaFold2-based structural modeling, molecular dynamics, and evolutionary features to identify and interpret oncogenic hotspot mutations in tumor suppressors and oncogenes. First author, bioRxiv (2022). Advisor: Raul Rabadan.
2025–present
Eureka: AI-assisted genomic discovery
Developed a platform integrating literature, genetic, regulatory, and structural evidence for variant interpretation and therapeutic target prioritization. Built benchmarks with controls for information leakage to evaluate target prioritization and enrichment for clinical success.
2017–2020
Developed a multiscale framework to prioritize regulatory elements, genes, pathways, and transcription-factor programs from whole-genome sequencing. Applied it to Hirschsprung disease; collaborators experimentally validated candidate mechanisms. The Chinese University of Hong Kong; advisor: Kevin Yip.
2018–2019
Developed and interpreted a semi-supervised framework integrating physical and regulatory interactions in heterogeneous biological networks. The Chinese University of Hong Kong; advisor: Kevin Yip.
2020
Performed genome-wide association analyses of susceptibility variants in a Han Chinese population. WeGene, Shenzhen Zaozhidao Company.
Peer-Reviewed Research Articles
Published as Fu, X. and Fu, A. X. *Equal contribution; †corresponding author.
Fu, X.*†, Mo, S.*, Buendia, A.*, et al.
Nature 637, 965–973 (2025)
Fu, A. X., Lui, K. N.-C., Tang, C. S.-M., et al.
Genome Research 30, 1618–1632 (2020)
Su, J., Reynier, J.-B., Fu, X., et al.
Genome Biology 24, 291 (2023)
Hypomorphic and dominant-negative impact of truncated SOX9 dysregulates Hedgehog-Wnt signaling, causing campomelia
Au, T. Y. K., Yip, R. K. H., Wynn, S. L., Tan, T. Y., Fu, A. X., et al.
PNAS 120, e2208623119 (2023)
Genome-wide association analyses identified novel susceptibility loci for pulmonary embolism among Han Chinese population
Zhang, Z., Li, H., …, Fu, X., et al.
BMC Medicine 21, 153 (2023)
A unified framework for integrative study of heterogeneous gene regulatory mechanisms
Cao, Q., Zhang, Z., Fu, A. X., et al.
Nature Machine Intelligence 2, 447–456 (2020)
Identification of genes associated with Hirschsprung disease, based on whole-genome sequence analysis, and potential effects on enteric nervous system development
Tang, C. S.-M., Li, P., Lai, F. P.-L., Fu, A. X., et al.
Gastroenterology 155, 1908–1922.e5 (2018)
Dual roles of an Arabidopsis ESCRT component FREE1 in regulating vacuolar protein transport and autophagic degradation
Gao, C., Zhuang, X., Cui, Y., Fu, X., et al.
PNAS 112, 1886–1891 (2015)
Reviews and Perspectives
Alvarez-Torres, M. d. M., Fu, X., and Rabadan, R.
Cancer Research 85, 2368–2375 (2025)
Fu, X. and Rabadan, R.
The Oncologist 29, 653–657 (2024)
Preprints and Unpublished Manuscripts
Hayward, S. B., Vaitsiankova, A., …, Fu, X., …, and Ciccia, A.
Accepted in principle, Nature Biotechnology. Preprint: bioRxiv (2026)
Tan, J.*, Fu, X.*, Ling, X.*, et al.
bioRxiv (2025; revised January 18, 2026)
Fu, X., Reglero, C., Swamy, V., et al.
bioRxiv (2022)
Nucleosome-scale p53–hormone receptor grammar links cancer and primate evolution
Fu, X.*†, Cai, Q.*, Satya, P., Rabadan, R.†, and Levine, A. J.†
Unpublished manuscript (2026)
Workshop Contributions
Multi-modal self-supervised pre-training for large-scale genome data
Mo, S., Fu, X., Hong, C., et al.
NeurIPS AI for Science Workshop (2021)
Invited Talks
Nov 2025
Columbia University: AI at VP&S Workshop - Foundation Models Across Scales
Jul 2025
Google Genomics
Jun 2025
Cancer Convergence Education Network / University of Chicago
Mar 2025
New York University
Feb 2025
Stanford University
Feb 2025
Genentech
Feb 2025
Tsinghua University
Jan 2025
EMBL Heidelberg
Jan 2025
Sanford Burnham Prebys Medical Discovery Institute
Nov 2024
Cancer Convergence Education Network / Spanish National Cancer Research Centre
May 2024
Cancer Convergence Education Network / University of Rome
Dec 2023
Cancer Convergence Education Network / Universitat Politecnica de Catalunya
Oct 2023
Cancer Convergence Education Network / Keio University