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Challenges in Computational Analysis of Mass Spectrometry Data for Proteomics 被引量:1

Challenges in Computational Analysis of Mass Spectrometry Data for Proteomics
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摘要 Mass spectrometry is an analytical technique for determining the composition of a sample. Recently it has become a primary tool for protein identification and quantification, and post translational modification characterization in proteomics research. Both the size and the complexity of the data produced by this experimental technique impose great computational challenges in the data analysis. This article reviews some of these challenges and serves as an entry point for those who want to study the area in general. Mass spectrometry is an analytical technique for determining the composition of a sample. Recently it has become a primary tool for protein identification and quantification, and post translational modification characterization in proteomics research. Both the size and the complexity of the data produced by this experimental technique impose great computational challenges in the data analysis. This article reviews some of these challenges and serves as an entry point for those who want to study the area in general.
作者 马斌
出处 《Journal of Computer Science & Technology》 SCIE EI CSCD 2010年第1期107-123,共17页 计算机科学技术学报(英文版)
基金 supported by the National High-Tech Research and Development 863 Program of China under Grant No.2008AA02Z313 NSERC RGPIN under Grant No. 238748-2006 a start up grant at University of Waterloo
关键词 mass spectrometry PROTEOMICS BIOINFORMATICS mass spectrometry, proteomics, bioinformatics
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