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.

CN119601085BActive Publication Date: 2025-09-19HUAZHONG AGRI UNIV
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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

Technical Problem

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.

Method used

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.

Benefits of technology

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.

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Abstract

This application relates to the field of maize gene prediction technology, specifically to methods, devices, and equipment for discovering pleiotropic maize genes. In an embodiment, a fully connected neural network model is trained using samples composed of gene expression properties and integrative omics network properties to discover pleiotropic genes from unknown genes that can balance maize growth and development and respond to environmental stress. This method, device, and equipment effectively reduces the risk of misidentification of irrelevant genes, ensures that the selected candidate genes have high functional relevance, and provides a more efficient verification basis.
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