DCMF-PPI: a protein-protein interaction predictor based on dynamic condition and multi-feature fusion
We conducted comprehensive experiments on benchmark datasets demonstrating that DCMF-PPI outperforms state-of-the-art methods in PPI prediction, achieving significant improvements in accuracy, precision, and recall. The framework's ability to fuse dynamic conditions and multi-level features highlights its effectiveness in modeling real-world biological complexities, positioning it as a robust tool for advancing PPI research and downstream applications in systems biology and drug discovery.
Authors
- Wenqing Yu (ORCID: https://orcid.org/0000-0002-3046-4485)
- Siqi Chen (ORCID: https://orcid.org/0000-0002-2460-4381)
- Chao Zhan (ORCID: https://orcid.org/0000-0001-5732-8857)
- Ang Zheng (ORCID: https://orcid.org/0000-0003-1078-6660)
Institutions
- Harbin Medical University (CN)
- Third Affiliated Hospital of Harbin Medical University (CN)
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Chongqing Jiaotong University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-10-15
- DOI
- https://doi.org/10.1186/s12859-025-06272-4
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China