Background: The computer-assisted detection of small molecules by mass spectrometry in biological samples provides a snapshot of thousands of peptides, protein fragments and proteins in biological samples. This new analytical technology has the potential to identify disease associated proteomic patterns in blood serum. However, the presently available bioinformatic tools are not sensitive enough to identify clinically important low abundant proteins as hormons or tumor markers with only low blood concentrations. Aim: Find, analyze and compare serum proteom patterns in groups of human subjects having different properties such as disease status with a new workflow to enhance sensitivity and specificity. Problems: Mass data acquired from high-throughput platforms frequently are blurred and noisy. This complicates the reliable identification of peaks in general and very small peaks even below noise level in particular.4 However, this statement is only valid for single or few spectra. If t...
Tim O. F. Conrad, Alexander Leichtle, Andre Hageh&