Insect multi-tissue expression amount prediction method and system based on multi-modal feature fusion

By employing a multimodal feature fusion method, combined with DNA regulatory sequences, RNA stability, and protein language models, the problems of multi-tissue output and cross-species adaptation in insect gene expression prediction were solved, achieving more accurate gene expression prediction and making it suitable for insect tissue-resolution expression profile reconstruction.

CN122090926BActive Publication Date: 2026-07-24ZHEJIANG NISHEN BIOMATERIALS CO LTD
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Patent Information

Application Number
CN202610559968.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-04-27
Publication Date
2026-07-24
Estimated Expiration
2046-04-27

AI Technical Summary

Technical Problem

Existing technologies for predicting gene expression levels in insects suffer from problems such as insufficient single-modal input, insufficient cross-species adaptation, difficulty in processing multi-tissue output, improper handling of missing tags, and lack of introduction of protein function conservation, resulting in unstable prediction results and large errors.

Method used

A multimodal feature fusion method is adopted, which combines DNA regulatory sequences, RNA stability features and pre-trained protein language model embeddings. A multi-tower deep learning network is used for joint modeling to output gene expression predictions for multiple tissues. Species embedding vectors are introduced to handle missing protein information, and species-tissue bias terms are used to compensate for expression differences.

Benefits of technology

It enables more accurate and comprehensive prediction of gene expression levels in multiple tissues of insects, and is suitable for tissue-resolution expression profile reconstruction in insects, improving the stability and accuracy of cross-species and multi-tissue prediction.

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Abstract

The present application relates to a kind of based on multi-modal feature fusion insect multi-tissue expression quantity prediction method and system, with target gene as basic prediction unit, while inputting the regulatory sequence information, RNA stability characteristic information and protein representation information of target gene, carry out joint modeling by multi-tower deep learning network, output the expression quantity prediction value of the target gene in multiple tissues.Advantage: break through the limitation of traditional method mainly relying on single mode data, first embed uniform into an expression prediction framework for insect gene regulatory sequence, RNA stability characteristic and pre-training protein language model;Using multi-modal prediction model, the multi-modal data features are extracted, fused and predicted, so as to provide accurate and comprehensive gene expression prediction results, while introducing a gating back mechanism for missing protein annotation, avoiding missing values being treated as zero or noise, so as to ensure the stability of prediction.
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