Biomolecular sequence searching method and apparatus, device, and storage medium
By using deep learning and efficient similarity search algorithms, biomolecular sequences are converted into vector representations and a vector database is constructed. This solves the problems of low computational efficiency and insufficient accuracy of existing tools in large-scale databases, and achieves fast and accurate homologous sequence identification.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- TENCENT TECHNOLOGY (SHENZHEN) CO LTD
- Filing Date
- 2025-11-20
- Publication Date
- 2026-06-04
AI Technical Summary
Existing homology search tools are computationally inefficient and struggle to accurately capture sequence similarities when dealing with large-scale biomolecular sequences, failing to meet the needs of modern biological research.
Using deep learning methods, biomolecular sequences are converted into vector representations through sequence coding models. Then, an efficient similarity search algorithm is used to construct a biomolecular sequence vector database, which stores the vector representations of known sequences and performs similarity calculations and screening of homologous sequences.
It improves the accuracy and efficiency of homologous biological sequence searching, enabling rapid identification of homologous sequences in large-scale databases and meeting the needs of biological research.
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