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分子组织生物学的空间组成部分。

Spatial components of molecular tissue biology.

机构信息

Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.

TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.

出版信息

Nat Biotechnol. 2022 Mar;40(3):308-318. doi: 10.1038/s41587-021-01182-1. Epub 2022 Feb 7.

Abstract

Methods for profiling RNA and protein expression in a spatially resolved manner are rapidly evolving, making it possible to comprehensively characterize cells and tissues in health and disease. To maximize the biological insights obtained using these techniques, it is critical to both clearly articulate the key biological questions in spatial analysis of tissues and develop the requisite computational tools to address them. Developers of analytical tools need to decide on the intrinsic molecular features of each cell that need to be considered, and how cell shape and morphological features are incorporated into the analysis. Also, optimal ways to compare different tissue samples at various length scales are still being sought. Grouping these biological problems and related computational algorithms into classes across length scales, thus characterizing common issues that need to be addressed, will facilitate further progress in spatial transcriptomics and proteomics.

摘要

用于以空间分辨方式分析 RNA 和蛋白质表达的方法正在迅速发展,这使得全面描述健康和疾病状态下的细胞和组织成为可能。为了最大限度地利用这些技术获得的生物学见解,关键是既要清楚地阐明组织空间分析中的关键生物学问题,又要开发解决这些问题所需的计算工具。分析工具的开发者需要确定需要考虑的每个细胞的内在分子特征,以及如何将细胞形状和形态特征纳入分析中。此外,还在寻找比较不同组织样本在不同长度尺度上的最佳方法。将这些生物学问题和相关的计算算法按长度尺度分类,从而描述需要解决的常见问题,将促进空间转录组学和蛋白质组学的进一步发展。

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