Computational Methods for Single-Cell Proteomics.

IF 7 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Annual Review of Biomedical Data Science Pub Date : 2023-08-10 Epub Date: 2023-04-11 DOI:10.1146/annurev-biodatasci-020422-050255
Sophia M Guldberg, Trine Line Hauge Okholm, Elizabeth E McCarthy, Matthew H Spitzer
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Abstract

Advances in single-cell proteomics technologies have resulted in high-dimensional datasets comprising millions of cells that are capable of answering key questions about biology and disease. The advent of these technologies has prompted the development of computational tools to process and visualize the complex data. In this review, we outline the steps of single-cell and spatial proteomics analysis pipelines. In addition to describing available methods, we highlight benchmarking studies that have identified advantages and pitfalls of the currently available computational toolkits. As these technologies continue to advance, robust analysis tools should be developed in tandem to take full advantage of the potential biological insights provided by these data.

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单细胞蛋白质组学的计算方法。
单细胞蛋白质组学技术的进步已经产生了由数百万细胞组成的高维数据集,这些数据集能够回答有关生物学和疾病的关键问题。这些技术的出现促使计算工具的发展,以处理和可视化复杂的数据。在这篇综述中,我们概述了单细胞和空间蛋白质组学分析管道的步骤。除了描述可用的方法外,我们还强调了基准测试研究,这些研究已经确定了当前可用的计算工具包的优点和缺点。随着这些技术的不断进步,应该同时开发强大的分析工具,以充分利用这些数据提供的潜在生物学见解。
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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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