军事医学2025，Vol.49Issue(3)：178-184,7.DOI:10.7644/j.issn.1674-9960.2025.03.003
基于转录组数据和基因本体知识的化合物毒性预测
Compound toxicity prediction based on transcriptomics data and gene ontology knowledge
摘要
Abstract
Objective To develop a new model for predicting compound toxicity and exploring related toxicity mechanisms using transcriptomic data and gene ontology knowledge.Methods Using the TOXRIC database,two toxicity-related datasets were constructed and a Tox VNN model was established that incorporated gene ontology knowledge to evaluate compound toxicity and identify key biological processes.Results Tox VNN demonstrated good predictability.The identification of important biological processes related to CYP enzyme activity and p53 pathway stress response provided insights into the toxicity mechanisms.Conclusion The Tox VNN,which integrates data and knowledge,can not only ensure high predictability,but also effectively identify important biological processes related to toxicity.This model offers a new approach to predicting and understanding compound toxicity in drug safety evaluation.关键词
化合物毒性预测/CYP酶活性/p53通路应激反应/转录组/基因本体/深度学习Key words
compound toxicity prediction/CYP enzyme activity/p53 pathway stress response/transcriptome/gene ontology/deep learning分类
药学引用本文复制引用
赵彩芸,何松,金义光,伯晓晨..基于转录组数据和基因本体知识的化合物毒性预测[J].军事医学,2025,49(3):178-184,7.基金项目
国家重点研发计划资助(SQ2024YFA1300245) （SQ2024YFA1300245）
