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使用文本挖掘资源推进新蛋白质的过敏性评估
Jorge Novoa1, Antonio Fernandez-Dumont2, E N Clare Mills3
1Computational Systems Biology Group, National Centre for Biotechnology (CNB-CSIC), 28049, Madrid, Spain.
概括
这项研究通过分析科学文献,创造了一个新的资源,通过分析科学文献,将过敏原与他们的症状联系起来. 这有助于更好地了解蛋白质安全性和过敏症状.
科学领域:
- 生物医学信息学 生物医学信息学
- 过敏基因组学 过敏基因组学
- 计算生物学 计算生物学
背景情况:
- 鉴于对替代蛋白质的需求日益增加,评估蛋白质的安全性,特别是对过敏原的潜力至关重要.
- 目前的过敏原数据库缺乏协调的临床信息,阻碍了系统研究.
- 缺少标准化的症状学数据,阻止与其他生物医学资源的整合.
研究的目的:
- 开发第一个全面的资源,注释过敏原症状学.
- 为未来精选编译与过敏原相关的临床数据建立基础.
- 提高对与过敏原相关的人类健康影响的理解.
主要方法:
- 在PubMed摘要 (∼3600万) 上使用了文本挖掘方法.
- 鉴定出过敏原和临床症状之间具有统计学意义的相关性.
- 从人类表型本体学和MeSH术语中提取了1,180个临床征兆.
主要成果:
- 将1,180个临床症状与1,036个独特的过敏原联系起来.
- 确定了14009种过敏原与其症状之间的关系.
- 为该资源开发了一个公开可用的交互式Web界面.
结论:
- 生成的资源提供了对过敏原症状学的全新,全面的注释.
- 该资源有助于将过敏原数据与健康研究的临床信息联系起来.
- 它作为进一步研究过敏原安全和管理的宝贵起点.
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