解读2型糖尿病中的基因疾病关联:一个精心策划的数据集,用于基于文本挖掘的分类
Sushrutha Raj1, Sushmitha Raj2, Vindhya Namdeo2
1Amity Institute of Integrative Sciences and Health, Amity University Haryana, Amity Education Valley, Gurgaon 122413, India.
Data in brief
|May 6, 2024
概括
这项研究建立了一个精选的数据集,将2型糖尿病 (T2D) 与特定基因联系起来. 本资源有助于培训文本挖掘分类器来预测疾病基因关联,这对于理解T2D遗传学至关重要.
科学领域:
- 遗传学 遗传学 是一个
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 2型糖尿病 (T2D) 是一个主要的全球健康问题,对死亡率有很大贡献,超过50亿受影响的个人.
- 遗传因素在T2D的发病和进展中起着关键作用,需要更深入地了解基因与疾病的关联.
- 现有研究强调了遗传倾向和T2D发展之间的复杂相互作用.
研究的目的:
- 为治疗2型糖尿病 (T2D) 的标准疾病基因关联数据集.
- 为培训基于文本挖掘的生物文献分类器提供参考数据.
- 为了促进T2D相关基因的预测和分析.
主要方法:
- 从PubMed使用EDirect. 下载了与T2D相关的摘要.
- 预处理摘要以提取含有疾病基因关联信息的参考句子.
- 手动验证的提取数据分为四个类别:是,不,模糊和X.
主要成果:
- 编制了对T2D的疾病基因关联的验证数据集.
- 将协会分为积极的,消极的,模糊的和无关的类别.
- 建立了一个基础数据集,用于培训和验证文本挖掘分类器.
结论:
- 精心策划的数据集是生物文学中文本挖掘的宝贵资源.
- 已开发的分类器可以预测T2D基因关联,并可扩展到其他疾病.
- 这项工作通过识别正相关基因来支持对T2D的深入系统级分析.
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