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Algorithms and Design Strategies Towards Automated Glycoproteomics Analysis

机译:自动化人体糖组学分析的算法和设计策略

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摘要

Glycoproteomics involves the study of the glycosylation events on protein sequences ranging from purified proteins to whole proteome scales. Understanding these complex post-translational modification (PTM) events requires elucidation of the glycan moieties (monosaccharide sequences and glycosidic linkages between residues), protein sequences, as well as site-specific attachment of glycan moieties onto protein sequences, in a spatial and temporal manner in a variety of biological contexts. Compared with proteomics, bioinformatics for glycoproteomics is immature and many researchers still rely on tedious manual interpretation of glycoproteomics data. As sample preparation protocols and analysis techniques have matured, the number of publications on glycoproteomics bioinformatics has increased substantially; however, the lack of consensus on tool development and code reuse limits the dissemination of bioinformatics tools because it requires significant effort to migrate a computational tool tailored for one method design to alternative methods. This review discusses algorithms and methods in glycoproteomics, and refers to the general proteomics field for potential solutions. It also introduces general strategies for tool integration and pipeline construction in order to better serve the glycoproteomics community.
机译:糖皮质激素学涉及对蛋白质序列糖基化事件的研究,从纯化的蛋白质到整个蛋白质组规模。了解这些复杂的翻译后修饰(PTM)事件需要以空间和时间的方式阐明聚糖部分(单糖序列和残基之间的糖苷键),蛋白质序列,以及聚糖部分在蛋白质序列上的位点特异性附着在各种生物学环境中。与蛋白质组学相比,用于糖蛋白组学的生物信息学还不成熟,许多研究人员仍然依赖于繁琐的糖蛋白组学数据人工解释。随着样品制备方案和分析技术的成熟,糖蛋白组学生物信息学的出版物数量大大增加。但是,在工具开发和代码重用方面缺乏共识,限制了生物信息学工具的传播,因为要为一种方法设计量身定制的计算工具迁移到替代方法需要大量的精力。这篇综述讨论了糖蛋白组学中的算法和方法,并为潜在的解决方案参考了通用的蛋白组学领域。它还介绍了工具集成和管道构建的一般策略,以便更好地服务于糖蛋白组学界。

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  • 期刊名称 other
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  • 年(卷),期 -1(36),4
  • 年度 -1
  • 页码 475–498
  • 总页数 47
  • 原文格式 PDF
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