More Information

ZhangLab - Kunming Institute of Zoology

Our laboratory specializes in computational biology and AI applications for genomics, with a focus on single-cell and spatial transcriptomics analysis.

Lab GitHub Repository:
https://github.com/ZhangLab-Kiz
Lab Homepage:
Kunming Institute of Zoology, Chinese Academy of Sciences
Kunming, Yunnan, China

Corresponding Author

Dr. Chao Zhang
Email: zhangchao@mail.kiz.ac.cn
Position: Principal Investigator, Computational Biology
Affiliation: Kunming Institute of Zoology, Chinese Academy of Sciences

Contributing Authors & Contacts

Tool Updates & Corrections:
Email: lishixin@mail.kiz.ac.cn
Email: xiaotianxiang251@mails.ucas.ac.cn
Email: lanyuanyuan22@mails.ucas.ac.cn

📄 Citing This Review

If you use this review or the website in your research, please cite:

S. Li, T. Xiao, Y. Lan, et al. "Artificial Intelligence Revolution in Transcriptomics: From Single Cells to Spatial Atlases." Adv. Sci. (2025): e18949.
DOI: https://doi.org/10.1002/advs.202518949

đŸ”Ŧ Research Focus Areas

Single-cell Analysis

AI methods for scRNA-seq, clustering, cell type identification

Spatial Transcriptomics

Spatial clustering, segmentation, integration methods

Foundation Models

Large-scale pre-training, transfer learning, generalization

AI Agents

LLM integration, automated pipelines, workflow automation

ℹī¸ About This Website

This website serves as an interactive supplement to our comprehensive review on AI methods in transcriptomics. It provides:

Last Updated: November 2025

🔗 Quick Links

Back to Home scRNA-seq Methods Spatial Transcriptomics Foundation Models AI Agents

📝 Feedback & Support

We welcome feedback, corrections, and suggestions for improving this review and website. Please contact us at any of the email addresses listed above or open an issue on our GitHub repository.

For specific tool recommendations or missing method reports, please reach out to our editorial team at lishixin@mail.kiz.ac.cn