An AI-based virus-host RNA sequence classification method and device

By employing a two-step filtering and AI classification method, combined with host genome mapping and an LSTM model, the problem of distinguishing viral RNA sequences from host RNA sequences was solved, achieving efficient and accurate viral sequence classification and identification of unknown viruses.

CN120977392BActive Publication Date: 2026-05-12BEIJING LINGWEI TECHNOLOGY DEVELOPMENT CO LTD
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Patent Information

Application Number
CN202511105123.6
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-08-07
Publication Date
2026-05-12
Estimated Expiration
2045-08-07

AI Technical Summary

Technical Problem

Existing technologies are insufficient for efficiently distinguishing between viral RNA sequences and host RNA sequences. Conventional methods are computationally intensive, time-consuming, and costly, making it difficult to screen for unknown viruses.

Method used

A two-step filtering and AI classification method was adopted. First, the host genome was used for filtering, then sequences longer than 1000 bp were assembled and screened, and the viral RNA sequence was classified using an LSTM model.

Benefits of technology

It significantly reduces computational load, alleviates hardware pressure, enhances virus identification capabilities, enables efficient and accurate virus sequence classification, and rapidly identifies unknown viruses.

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Abstract

The application discloses a virus-host RNA sequence classification method and device based on AI, and relates to the field of biological detection.The method comprises the following steps: mapping preprocessed short read RNA sequences to a host genome twice, assembling short read RNA sequences which are not mapped to the host genome into continuous RNA sequences, and screening RNA sequences with a length greater than 1000bp from the continuous RNA sequences; and performing AI classification on the RNA sequences with a length greater than 1000bp to obtain virus RNA sequences.The application combines host filtering, rapid assembly and AI classification, can significantly reduce the calculation amount and hardware pressure, realizes efficient and accurate virus sequence classification, and can quickly distinguish unknown viruses.
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