About SynLeaF

Platform Overview

SynLeaF is a research platform for synthetic lethality prediction and search. It provides candidate gene pairs and supports both pan-cancer and specific cancer types. The content is for research only and is not medical advice.

Data Sources

We integrate public multi-omics data and synthetic lethality resources. Please follow the citation and license rules of each source.

• Multi-omics data:
  • Data types: gene expression, mutation, CNV, methylation.
  • Cancer studies: BRCA, CESC, COAD, KIRC, LAML, LUAD, OV, SKCM, Pan-cancer.
• SynLethDB 2.0: Synthetic lethality knowledge graph and relations (Download).
• Cancer-specific SL datasets: (Download).

Software, Libraries, and Services

This site is built with:

• Frontend: HTML / CSS / JavaScript
• Deployment: Nginx (HTTP server)

Code repository: GitHub

License

Unless stated otherwise, all page and document content is licensed under Creative Commons Attribution 4.0 (CC BY 4.0). Licenses for code, models, and data will follow our open-source policies and upstream terms.

How to Cite

If you find SynLeaF useful in your research, please cite our paper:

• Xing, Z., Zhou, S., Wang, R., Han, R., Zhang, S., Chen, S., Huang, Y., Ma, J., Chen, Y., Wang, X., Wang, Y. & Li, J. SynLeaF: A Dual-Stage Multimodal Fusion Framework for Synthetic Lethality Prediction Across Pan- and Single-Cancer Contexts. arXiv:2603.22369 [q-bio.GN] (2026). https://arxiv.org/abs/2603.22369.

BibTeX:

@misc{SynLeaF2026,
          title={SynLeaF: A Dual-Stage Multimodal Fusion Framework for Synthetic Lethality Prediction Across Pan- and Single-Cancer Contexts},
          author={Zheming Xing and Siyuan Zhou and Ruinan Wang and Rui Han and Shiming Zhang and Shiqu Chen and Yurui Huang and Jiahao Ma and Yifan Chen and Xuan Wang and Yadong Wang and Junyi Li},
          year={2026},
          eprint={2603.22369},
          archivePrefix={arXiv},
          primaryClass={q-bio.GN},
          url={https://arxiv.org/abs/2603.22369},
        }

Related Publications

1. Struct2SL: Synthetic lethality prediction based on AlphaFold2 structure information and Multilayer Perceptron. Huang Y, Yuan R, Li Y, Xing Z and Li J. Computational and Structural Biotechnology Journal. 2025 April; doi.org/10.1016/j.csbj.2025.04.012.
2. SLGNNCT: Synthetic lethality prediction based on knowledge graph for different cancers types. Chen J, Pan J, Zhu Y, Li J. ICIC 2024 : International Conference On Intelligent Computing, Tianjin, China, 2024.8.
3. SLGNN: Synthetic lethality prediction in human cancers based on factor-aware knowledge graph neural network. Zhu Y, Zhou Y, Liu Y, Wang X, Li J. Bioinformatics. 2023 January; doi:10.1093/bioinformatics/btad015.

Contact

Address
School of Computer Science and Technology,
Harbin Institute of Technology (Shenzhen),
Shenzhen, Guangdong 518055, China.

Email
lijunyi@hit.edu.cn