{"title":"第二章。从头肽测序","authors":"B. Ma","doi":"10.1039/9781782626732-00015","DOIUrl":null,"url":null,"abstract":"De novo peptide sequencing refers to the process of determining a peptide’s amino acid sequence from its MS/MS spectrum alone. The principle of this process is fairly straightforward: a high-quality spectrum may present a ladder of fragment ion peaks. The mass difference between every two adjacent peaks in the ladder is used to determine a residue of the peptide. However, most practical spectra do not have sufficient quality to support this straightforward process. Therefore, research in de novo sequencing has largely been a battle against the errors in the data. This chapter reviews some of the major developments in this field. The chapter starts with a quick review of the history in Section 1. Then manual de novo sequencing is examined in Section 2. Section 3 introduces a few commonly used de novo sequencing algorithms. An important aspect of automated de novo sequencing software is a good scoring function that serves as the optimization goal of the algorithm. Thus, Section 4 is devoted for the methods to define good scoring functions. Section 5 reviews a list of relevant software. The chapter concludes with a discussion of the applications and limitations of de novosequencing in Section 6.","PeriodicalId":192946,"journal":{"name":"Proteome Informatics","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Chapter 2. De novo Peptide Sequencing\",\"authors\":\"B. Ma\",\"doi\":\"10.1039/9781782626732-00015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"De novo peptide sequencing refers to the process of determining a peptide’s amino acid sequence from its MS/MS spectrum alone. The principle of this process is fairly straightforward: a high-quality spectrum may present a ladder of fragment ion peaks. The mass difference between every two adjacent peaks in the ladder is used to determine a residue of the peptide. However, most practical spectra do not have sufficient quality to support this straightforward process. Therefore, research in de novo sequencing has largely been a battle against the errors in the data. This chapter reviews some of the major developments in this field. The chapter starts with a quick review of the history in Section 1. Then manual de novo sequencing is examined in Section 2. Section 3 introduces a few commonly used de novo sequencing algorithms. An important aspect of automated de novo sequencing software is a good scoring function that serves as the optimization goal of the algorithm. Thus, Section 4 is devoted for the methods to define good scoring functions. Section 5 reviews a list of relevant software. The chapter concludes with a discussion of the applications and limitations of de novosequencing in Section 6.\",\"PeriodicalId\":192946,\"journal\":{\"name\":\"Proteome Informatics\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proteome Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1039/9781782626732-00015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proteome Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1039/9781782626732-00015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
De novo peptide sequencing是指仅从肽的MS/MS谱确定肽的氨基酸序列的过程。这个过程的原理相当简单:一个高质量的光谱可能呈现一个片段离子峰的阶梯。梯子中每两个相邻峰之间的质量差用于确定肽的残基。然而,大多数实际的光谱没有足够的质量来支持这个简单的过程。因此,从头测序的研究在很大程度上是一场与数据错误的斗争。本章回顾了这一领域的一些主要发展。本章以第1节对历史的快速回顾开始。然后在第2节中检查手动从头测序。第3节介绍了几种常用的从头排序算法。自动化从头测序软件的一个重要方面是良好的评分功能,作为算法的优化目标。因此,第4节将专门介绍定义好的评分函数的方法。第5节回顾了相关软件的列表。本章最后在第6节讨论了de novosequencing的应用和局限性。
De novo peptide sequencing refers to the process of determining a peptide’s amino acid sequence from its MS/MS spectrum alone. The principle of this process is fairly straightforward: a high-quality spectrum may present a ladder of fragment ion peaks. The mass difference between every two adjacent peaks in the ladder is used to determine a residue of the peptide. However, most practical spectra do not have sufficient quality to support this straightforward process. Therefore, research in de novo sequencing has largely been a battle against the errors in the data. This chapter reviews some of the major developments in this field. The chapter starts with a quick review of the history in Section 1. Then manual de novo sequencing is examined in Section 2. Section 3 introduces a few commonly used de novo sequencing algorithms. An important aspect of automated de novo sequencing software is a good scoring function that serves as the optimization goal of the algorithm. Thus, Section 4 is devoted for the methods to define good scoring functions. Section 5 reviews a list of relevant software. The chapter concludes with a discussion of the applications and limitations of de novosequencing in Section 6.