Two-Stage Model-Based Clustering for Liquid Chromatography Mass Spectrometry Data Analysis

Abstract

Proteomic mass spectrometry is gaining an increasing role in diagnostics and in studies on protein complexes and biological systems. This experimental technology is producing high-throughput data which is inherently noisy and may contain various errors. Mathematical processing can help in removing them.