Modeling patient tissues at molecular resolution with Eva
Yufan Liu, Rishabh Sharma, Matthew Bieniosek, Amy Kang, Eric Wu, Peter Chou, Irene Li, Maha Rahim, Erica Bauer, Ran Ji, Wei Duan, Li Qian, Ruibang Luo, Padmanee Sharma, Renu Dhanasekaran, Christian M. Schürch, Gregory Charville, Aaron T. Mayer, James Zou, Alexandro E. Trevino*, Zhenqin Wu*
preprint: 10.64898/2025.12.10.693553, code available at: https://github.com/YAndrewL/Eva
HOPE: Interpretable Histology Analysis with Spatial Omics-Derived Signatures for Precision Oncology
Tianyi Wang, Matthew Bieniosek, Tamara J. Krpicak, Mingyuan Luan, Benjamin Ruf, Christian M. Schürch, Aaron T. Mayer, Ruibang Luo, Alexandro E. Trevino, Zhenqin Wu
preprint in preparation, code available at: https://github.com/wangtyi/HOPE
Best student paper (extended abstract) at CVAMD@ICCV2025
OmicsNavigator: an auditable scientific partner for scalable hypothesis validation in spatial omics
Li Yiyao, Nirvi Vakharia, Weixin Liang, Aaron T. Mayer, Ruibang Luo, Alexandro E. Trevino, Zhenqin Wu.
preprint (v1): 10.1101/2025.07.21.665821, code and data available at: https://github.com/yyli-leo/OmicsAnnotator
Spatial multi-omics and deep learning reveal fingerprints of immunotherapy response and resistance in hepatocellular carcinoma
Zhenqin Wu, Joseph Boen, Sonali Jindal, Sreyashi Basu, Matthew Bieniosek, Siyu He, Michael LaPelusa, Aaron T Mayer, Ahmed O Kaseb, James Zou, Padmanee Sharma, Alexandro E Trevino
preprint: 10.1101/2025.06.11.656869, data available at: https://zenodo.org/records/15392699
ROSIE: AI generation of multiplex immunofluorescence staining from histopathology images
Eric Wu, Matthew Bieniosek, Zhenqin Wu, Nitya Thakkar, Gregory W. Charville, Ahmad Makky, Christian M. Schürch, Jeroen R. Huyghe, Ulrike Peters, Christopher I. Li, Li Li, Hannah Giba, Vivek Behera, Arjun Raman, Alexandro E. Trevino, Aaron T. Mayer and James Zou.
Nature Communications, 2025.
DOI: 10.1038/s41467-025-62346-0, preprint: 10.1101/2024.11.10.622859
Code available at: https://gitlab.com/enable-medicine-public/rosie
Characterizing tissue structures from spatial omics with spatial cellular graph partition
Zhenqin Wu, Ayano Kondo, Monee McGrady, Ethan A. G. Baker, Benjamin Chidester, Eric Wu, Maha K. Rahim, Nathan A. Bracey, Vivek Charu, Raymond J. Cho, Jeffrey B. Cheng, Maryam Afkarian, James Zou, Aaron T. Mayer, and Alexandro E. Trevino.
Cell Reports Methods, 2024.
DOI: 10.1016/j.crmeth.2024.100838, preprint:10.1101/2023.09.05.556133
Code available at: https://gitlab.com/enable-medicine-public/scgp, datasets available at: https://doi.org/10.5281/zenodo.12682727
Zhenqin Wu*, Alexandro E Trevino*, Eric Wu, Kyle Swanson, Honesty J Kim, H Blaize D’Angio, Ryan Preska, Gregory W Charville, Piero D Dalerba, Ann Marie Egloff, Ravindra Uppaluri, Umamaheswar Duvvuri, Aaron T Mayer, and James Zou.
Nature Biomedical Engineering, 2022
DOI: 10.1038/s41551-022-00951-w, preprint: 10.1101/2022.05.12.491707
Code available at: https://gitlab.com/enable-medicine-public/space-gm, datasets available at: https://doi.org/10.5281/zenodo.13179600
Associated Content:
Contributed talk at The 2022 ICML Workshop on Computational Biology
Learning spatial cellular motifs predictive of the responses of patients to cancer treatments, Research Briefing, Nature Biomedical Engineering
Identifying spatial cellular structures with SPACE-GM, Tools of the Trade, Nature Reviews Cancer
DynaMorph: self-supervised learning of morphodynamic states of live cells
Zhenqin Wu*, Bryant B Chhun*, Galina Popova*, Syuan-Ming Guo, Chang N Kim, Li-Hao Yeh, Tomasz Nowakowski, James Zou, and Shalin B Mehta.
Molecular Biology of the Cell, 2022
DOI: 10.1091/mbc.E21-11-0561, preprint: 10.1101/2020.07.20.213074, code available at: https://github.com/mehta-lab/dynamorph
Associated Content:
Presented at The 2021 ICML Workshop on Computational Biology
PB-Net: Automatic peak integration by sequential deep learning for multiple reaction monitoring
Zhenqin Wu, Daniel Serie, Gege Xu, and James Zou.
Journal of Proteomics, 2020
DOI: 10.1016/j.jprot.2020.103820, code available at: https://github.com/miaecle/PB-net
Associated Content:
Spotlight talk at The 2019 ICML Workshop on Computational Biology
InterVenn Biosciences Releases First-Ever Software for AI-Enabled Mass Spec Analysis, businesswire
Clinical Validation of the InterVenn Ovarian Cancer Liquid Biopsy, Clinical Trials, NCBI
MoleculeNet: a benchmark for molecular machine learning
Zhenqin Wu*, Bharath Ramsundar*, Evan N Feinberg, Joseph Gomes, Caleb Geniesse, Aneesh S Pappu, Karl Leswing, Vijay Pande
Chemical Science, 2018
DOI: 10.1039/C7SC02664A, preprint: 10.48550/arXiv.1703.00564, code available at: https://github.com/deepchem/deepchem