一种亚铁血红素结合位点预测方法、系统、介质和设备
By extracting multiple features of the protein and using hierarchical networks and multi-head attention mechanisms for analysis, the problem of insufficient prediction accuracy of heme binding sites in existing technologies has been solved, achieving higher prediction accuracy and generalization ability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- YANGTZE DELTA REGION INST (QUZHOU) UNIV OF ELECTRONIC SCI & TECH OF CHINA
- Filing Date
- 2025-11-24
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for predicting heme binding sites neglect the overall description of protein structure, resulting in poor prediction accuracy, especially for predicting specific functional sites of proteins.
By acquiring protein sequence and structural information, multiple physicochemical properties, amino acid embedding features, and protein secondary structure features are extracted. Hierarchical networks and multi-head attention mechanisms are used for feature fusion and analysis, including bidirectional long short-term memory neural networks and fully connected neural networks, to capture the contextual and local dependencies of protein sequences.
It significantly improves the prediction accuracy of heme binding sites and enhances the understanding and prediction capabilities of protein sequence features, especially in the accuracy and generalization ability of identifying heme binding sites.
Smart Images
Figure CN121565244B_ABST