Computational Approaches for Pathway-Centric Analysis of Protein Post-Translational Modifications.

IF 3.9 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Proteomics Pub Date : 2025-10-18 DOI:10.1002/pmic.70055
Julian Müller, Bernhard Kuster, Matthew The
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引用次数: 0

Abstract

Protein function is dynamically modulated by post-translational modifications (PTMs). Many different types of PTMs can nowadays be identified and quantified at a large scale using mass spectrometry. It is well known that many PTMs have an effect on protein function and cellular processes, and they should be studied not in isolation, but in the holistic context of cellular pathways. This is increasingly facilitated by a wide variety of computational efforts. This review aims to give a systematic overview of tools for pathway-centric analysis of PTM data and critically evaluate the state of play in this research field. Starting from databases that make up the foundational prior knowledge, we follow typical steps that an analytical workflow might contain, including pathway enrichment analysis, algorithms for pathway reconstruction, and the integration and visualization of results. We then reflect on common limitations of all existing tools and give our opinion on future directions that we think are currently most desirable.

以途径为中心的蛋白质翻译后修饰分析的计算方法。
蛋白质的功能是由翻译后修饰(PTMs)动态调节的。如今,许多不同类型的PTMs可以使用质谱法进行大规模鉴定和定量。众所周知,许多ptm对蛋白质功能和细胞过程有影响,它们不应该孤立地进行研究,而应该在细胞途径的整体背景下进行研究。各种各样的计算努力日益促进了这一点。本综述旨在对PTM数据的路径中心分析工具进行系统概述,并批判性地评估该研究领域的现状。从构成基础先验知识的数据库开始,我们遵循分析工作流可能包含的典型步骤,包括路径丰富分析,路径重建算法以及结果的集成和可视化。然后,我们反思所有现有工具的共同局限性,并对我们认为当前最理想的未来方向给出我们的意见。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Proteomics
Proteomics 生物-生化研究方法
CiteScore
6.30
自引率
5.90%
发文量
193
审稿时长
3 months
期刊介绍: PROTEOMICS is the premier international source for information on all aspects of applications and technologies, including software, in proteomics and other "omics". The journal includes but is not limited to proteomics, genomics, transcriptomics, metabolomics and lipidomics, and systems biology approaches. Papers describing novel applications of proteomics and integration of multi-omics data and approaches are especially welcome.
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