• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Annual meeting of the Association for Computational Linguistics;Workshop on biomedical natural language processing >CRF-LSTM Text Mining Method Unveiling the Pharmacological Mechanism of Off-target Side Effect of Anti-Multiple Myeloma Drugs
【24h】

CRF-LSTM Text Mining Method Unveiling the Pharmacological Mechanism of Off-target Side Effect of Anti-Multiple Myeloma Drugs

机译：CRF-LSTM文本挖掘方法揭示了抗多发性骨髓瘤药物脱靶副作用的药理机制

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Off-target effects played a vital role in the pharmacological understanding of drug efficacy and this research aimed to use text mining strategy to curate molecular level information and unveil the mechanism of off-target effect caused by the usage of anti-multiple myeloma (MM) drugs. After training a hybrid CNN-CRF-LSTM neural network upon the training data from TAC 2017 benchmark database, we extracted all of the side effects of 16 anti-MM drugs from drug labels, and combined the results with existed database. Afterwards, gene targets of anti-MM drugs were obtained by using structure similarity, and their related phenotypes were retrieved from Human Phenotype Ontology. Furthermore, linked phenotypes to candidate genes and adverse reaction of known drugs formed a knowledge graph. Through regulation analysis upon intersected phenotypes of drugs and target genes, an off-target effect caused by SLC7A7 was found, which with high possibility unveiled the pharmacological mechanism of side effect after using combination of anti-MM drugs.
机译：脱靶效应在药理学的药理学理解中起着至关重要的作用，本研究旨在使用文本挖掘策略来整理分子水平信息，并揭示使用抗多发性骨髓瘤（MM）引起的脱靶效应的机制。毒品。在根据TAC 2017基准数据库的训练数据训练了CNN-CRF-LSTM混合神经网络后，我们从药物标签中提取了16种抗MM药物的所有副作用，并将结果与​​现有数据库进行了合并。然后，通过结构相似性获得抗MM药物的基因靶标，并从人类表型本体论中检索其相关表型。此外，与候选基因相关的表型和已知药物的不良反应形成了一个知识图。通过对药物和靶基因相交表型的调控分析，发现由SLC7A7引起的脱靶作用，很有可能揭示了抗MM药物联合使用后的副作用的药理机制。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号