PAMPA:一个用于考古和古生物学缩放样本的肽标记和分类鉴定的软件。

IF 3.6 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Fabrice Bray,  and , Hélène Touzet*, 
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引用次数: 0

摘要

ZooMS (Zooarcheology by Mass Spectrometry,动物考古质谱法)是一种快速、经济的动物遗骸物种鉴定方法。质谱生成后,进行分类鉴定的一种常用方法是将质谱指纹图谱与诊断肽标记的参考数据库进行比较,以确定来源物种。然而,这个分析阶段是乏味的,容易出错,经常需要手工检查光谱。在本文中,我们提出了一种全面的方法来自动化和标准化使用肽标记和ZooMS光谱分类。我们已经开发了PAMPA(古代物种的蛋白质质谱分析)软件,我们使用MALDI-TOF和MALDI-FTICR生成的骨骼样本的各种光谱数据来证明其有效性。PAMPA是开源的,附带一个肽标记数据库和COL1A1和COL1A2序列的集合。我们相信这将是科学界的宝贵资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

PAMPA: A Software for Peptide Markers and Taxonomic Identification for ZooMS Samples in Archaeology and Paleontology

PAMPA: A Software for Peptide Markers and Taxonomic Identification for ZooMS Samples in Archaeology and Paleontology

ZooMS (Zooarcheology by Mass Spectrometry) is a rapid and cost-effective method for species identification of animal remains through peptide mass fingerprinting. After mass spectrum generation, a common way to perform taxonomic identification is to compare the mass fingerprints to a reference database of diagnostic peptide markers to determine the species of origin. This analytical stage, however, is tedious and error-prone, often necessitating a manual examination of spectra. In this article, we present a comprehensive approach to automate and standardize the usage of peptide markers and the classification of ZooMS spectra. We have developed software called PAMPA (protein analysis by mass spectrometry for ancient species), for which we demonstrate the effectiveness using a variety of spectral data from bone samples generated by MALDI-TOF and MALDI-FTICR. PAMPA is open source and comes with a database of peptide markers and a collection of curated COL1A1 and COL1A2 sequences. We believe it will be a valuable resource for the scientific community.

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来源期刊
Journal of Proteome Research
Journal of Proteome Research 生物-生化研究方法
CiteScore
9.00
自引率
4.50%
发文量
251
审稿时长
3 months
期刊介绍: Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".
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