Method, device and equipment for mining pleiotropic genes in corn
Through the fully connected neural network model and gene regulatory network, corn pleiotropic genes are automatically identified and verified, which solves the problem of difficulty in screening pleiotropic genes in existing technologies and improves the prediction accuracy and stress resistance of corn breeding.
Patent Information
- Application Number
- CN202411684295.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-22
- Publication Date
- 2025-09-19
- Estimated Expiration
- 2044-11-22
AI Technical Summary
Existing technologies make it difficult to effectively predict and screen pleiotropic genes, resulting in corn facing disease attacks, adverse environmental conditions and other growth and development disorders during its growth process, affecting its yield and quality.
By adopting a fully connected neural network model, combining gene expression properties and integrative omics network properties, and constructing gene regulatory networks and network subgraphs, we can automatically identify and verify potential pleiotropic genes, reduce the risk of misjudgment, and improve prediction accuracy.
It has achieved efficient screening and verification of corn multi-effect genes, improved the reliability of the predicted probability density curve, provided direct experimental data support for breeding work, and improved corn stress resistance and yield.