Computational methods for identifying gene networks containing functionally related genes

JP2025504387A5Pending Publication Date: 2025-10-31LIFEMINE THERAPEUTICS INC
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Patent Information

Application Number
JP2024541024
Authority / Receiving Office
JP · JP
Patent Type
Applications
Current Assignee / Owner
Priority Date
2022-01-07
Filing Date
2023-01-05
Publication Date
2025-10-31

AI Technical Summary

Technical Problem

The prior art has shortcomings in identifying biosynthetic gene clusters (BGCs), including difficulty in identifying BGCs without core synthesizers, dependence on the limitations of core enzymes, and inability to effectively link BGCs with secondary metabolites.

Method used

Computational methods are used to integrate coevolution, coregulation, colocalization and functional enrichment information, identify BGCs independent of core synthetases, and link BGCs with their potential downstream targets through functional correlation analysis, including determining functional correlation scores and functional category enrichment analysis in the gene network.

Benefits of technology

It improves the recognition accuracy and comprehensiveness of BGCs, can identify BGCs without core synthetases, and effectively links their potential downstream targets, enhancing the discovery and utilization of secondary metabolites.

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Abstract

We describe a computational method for identifying biosynthetic gene clusters (BGCs) independent of prior identification of core synthases. The disclosed method also facilitates linking BGCs to their potential downstream targets. The approach integrates information from co-evolution, co-occurrence, co-regulation, co-localization, and functional enrichment to group functionally related genes across gene networks, delineate BGCs, and propose putative secondary metabolite targets.
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