基于概率的肽质量指纹图谱蛋白质鉴定评分函数的设计与实现。

Design and implementation of probability-based scoring function for peptide mass fingerprinting protein identification.

作者信息

Song Zhao, Chen Luonan, Zhang Chao, Xu Dong

机构信息

Comput. Sci. Dept., Missouri Univ., Columbia, MO 65211-2060, USA.

出版信息

Conf Proc IEEE Eng Med Biol Soc. 2006;2006:4556-9. doi: 10.1109/IEMBS.2006.260150.

DOI:10.1109/IEMBS.2006.260150

PMID:17946250

Abstract

Protein identification through high-throughput mass spectrum data is an important domain in proteomics. Peptide mass fingerprinting (PMF) is one of the major methods for protein identification using the mass-spec technology. We developed a software package called "ProteinDecision" for PMF protein identification, together with a user-friendly graphical interface. "ProteinDecision" can handle the issues of selecting peaks from mass spectrum, transforming database format, displaying the top ranks of identification result, and detailed information for each ranking. We used a novel scoring function by considering the distribution of matching a mass-to-charge and peak intensity in a database based on the MOWSE table. Our new scoring function is assessed better than existing ones by comparing the computational results using experimental PMF data. A standalone version of "ProteinDecision" is freely available upon request.

摘要

通过高通量质谱数据进行蛋白质鉴定是蛋白质组学中的一个重要领域。肽质量指纹图谱（PMF）是使用质谱技术进行蛋白质鉴定的主要方法之一。我们开发了一个名为“ProteinDecision”的软件包用于PMF蛋白质鉴定，并带有一个用户友好的图形界面。“ProteinDecision”可以处理从质谱中选择峰、转换数据库格式、显示鉴定结果的排名靠前的结果以及每个排名的详细信息等问题。我们基于MOWSE表，通过考虑数据库中质荷比匹配和峰强度的分布，使用了一种新颖的评分函数。通过使用实验性PMF数据比较计算结果，我们的新评分函数比现有函数评估效果更好。可根据要求免费提供“ProteinDecision”的独立版本。