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首页> 外文会议>MEDINFO >Constructing a Gene-Drug-Adverse Reactions Network and Inferring Potential Gene-Adverse Reactions Associations Using a Text Mining Approach
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Constructing a Gene-Drug-Adverse Reactions Network and Inferring Potential Gene-Adverse Reactions Associations Using a Text Mining Approach

机译：使用文本挖掘方法构建基因 - 药物 - 不良反应网络和推断潜在基因 - 不良反应关联

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Our objective was to identify and extract gene-drug and drug-adverse drug reaction (ADR) relationships from different bio-medical literature collections, and to predict the possible association between gene and ADR. The drug, ADR and gene entities were recognized by a CRF model with multiple features. Logistic regression models were constructed for each drug-ADR and drug-gene pair based on its frequency. Mesh Rule association and similarity with known association etc. Using predicted score to generate drug- ADR matrix and drug-gene matrix, and then calculating for gene-ADR matrix. Network and clustering analysis were applied to verify and interpret the relationship between them. A total of 78014 potential gene-ADR associations were predicted. Part of the predicted results can be explained by the network-clustering-pathway analysis, and verified in the literature. The gene-drug-ADR network constructed in this study can provide a reference for the possible association between the gene and ADR.
机译：我们的目的是鉴定和提取来自不同生物医学文献收集的基因 - 药物和药物 - 不良药物反应（ADR）关系，并预测基因和ADR之间的可能关联。药物，ADR和基因实体被CRF模型识别，具有多种特征。基于其频率为每种药物-ADR和药物 - 基因对构建逻辑回归模型。网格规则关联和与已知关联等的相似性使用预测得分产生药物 - ADR基质和药物 - 基因基质，然后计算基因ADR基质。应用网络和群集分析来验证和解释它们之间的关系。总共预测了78014个潜在的基因ADR关联。可以通过网络聚类 - 途径分析来解释预测结果的一部分，并在文献中验证。本研究中构建的基因 - 药物ADR网络可以提供基因和ADR之间可能的关联的参考。

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