在转录组学中接近整体的转录组-卷积和解卷积
Maik Wolfram-Schauerte1, Thomas Vogel1, Hanati Tuoken2
1Faculty of Science, Department of Computer Science, Eberhard-Karls University Tübingen, Sand 14, D-72076 Tübingen, Baden-Württemberg, Germany.
Briefings in bioinformatics
|August 3, 2025
概括
本综述探讨了用于分析复杂组织中基因活性的转录组卷积和解卷积方法. 需要采用整体方法来克服数据的局限性,并改善单细胞和大量RNA-seq集成.
科学领域:
- 文字转录学 (Transcriptomics) 是一个学科.
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 组织包括具有独特基因活动的多样化的细胞群.
- 大量RNA测序 (RNA-seq) 测量了组织层面的基因活性.
- 病理过程改变了组织组成和细胞特异性基因表达,挑战了大量的RNA-seq分析.
研究的目的:
- 审查和比较现有的卷积和解卷积方法用于转录组分析.
- 引入"整体转录组模型",整合卷积和解卷积.
- 确定关键的挑战,并提出一个统一的框架,以推进该领域.
主要方法:
- 现有的单细胞和散装RNA-seq (de) 卷积方法的概述.
- 对 (解) 卷积方法的基准测试.
- 发表的 (解) 卷积研究的分析.
主要成果:
- 确定适合数据集的有限可用性是主要的瓶.
- 强调在模型评估和培训中使用不准确的方法.
- 证明了联合考虑卷积和解卷积的必要性.
结论:
- 一个整体的转录组模型整合卷积和解卷积是必不可少的.
- 提出了一个统一的框架,以促进协作进步.
- 解决数据的局限性和改进评估方法对于未来的进步至关重要.
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