精准医学的多主题数据整合和分析管道:系统性审查
Esraa Hamdi Abdelaziz1, Rasha Ismail1, Mai S Mabrouk2
1Faculty of Computer and Information Sciences, Ainshams University, Cairo, Egypt.
Computational biology and chemistry
|October 24, 2024
概括
多组学分析整合了用于精准医学的各种生物数据. 这一全面的审查涵盖了整个管道,从数据库和集成方法到解释,解决当前研究的局限性.
科学领域:
- 基因组学和生物信息学
- 翻译医学是一种翻译医学.
- 计算生物学 计算生物学
背景情况:
- 在捕捉生物复杂性的单一omics方法的局限性阻碍了精准医学的进步.
- 综合了DNA测序,RNA测序和质谱的数据,提供了对生物系统更全面的看法.
- 现有的审查往往侧重于多主题分析的特定方面,缺乏对整个管道的全面概述.
研究的目的:
- 为准确医学提供多学科数据分析管道的全面概述.
- 涵盖数据库,缩小维度,数据整合技术和下游应用.
- 讨论评估指标,模型可解释性和多omics集成的未来挑战.
主要方法:
- 对流行的多omics数据库的审查.
- 探索减小维度的技术.
- 详细研究数据整合方法及其应用.
- 讨论评估指标和模型可解释性的讨论.
主要成果:
- 确定关键的多学科数据库和计算方法.
- 数据整合策略的分类及其与下游分析的相关性,如癌症分类和生物标志物发现.
- 强调模型可解释性和评估指标对于强大的多经济学研究的重要性.
结论:
- 对多学科管道的全面理解对于推进精准医学至关重要.
- 解决数据集成和可解释性方面的挑战将提高多学科方法的临床实用性.
- 未来的研究应该专注于开发标准化,可解释和强大的多学科整合方法.
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