全生物数据集的单细胞分析。

IF 7 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Angela Oliveira Pisco, Bruno Tojo, Aaron McGeever
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引用次数: 4

摘要

细胞图谱是基因组的重要伙伴,因为它们阐明了基因如何以特定细胞类型的方式使用,或者基因的使用如何在生物体的一生中发生变化。这篇综述探讨了生物体单细胞图谱的最新进展,使我们能够理解健康和疾病中的细胞异质性、组织和细胞命运。在这里,我们概述了最近建立跨物种细胞图谱的努力,并讨论了该领域目前面临的挑战。此外,我们提出了一个概念,即拥有一个可以随着实验和计算方法的数量而扩展的知识库,以及一个新的反馈回路,用于包括用户贡献的计算方法的开发和基准测试。这两个方面是单细胞生物学社区努力的关键,这将有助于以无与伦比的分辨率产生细胞类型和状态的综合注释图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single-Cell Analysis for Whole-Organism Datasets.

Cell atlases are essential companions to the genome as they elucidate how genes are used in a cell type-specific manner or how the usage of genes changes over the lifetime of an organism. This review explores recent advances in whole-organism single-cell atlases, which enable understanding of cell heterogeneity and tissue and cell fate, both in health and disease. Here we provide an overview of recent efforts to build cell atlases across species and discuss the challenges that the field is currently facing. Moreover, we propose the concept of having a knowledgebase that can scale with the number of experiments and computational approaches and a new feedback loop for development and benchmarking of computational methods that includes contributions from the users. These two aspects are key for community efforts in single-cell biology that will help produce a comprehensive annotated map of cell types and states with unparalleled resolution.

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来源期刊
CiteScore
11.10
自引率
1.70%
发文量
0
期刊介绍: The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.
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