A numerical method for mass spectral data analysis

The new generation of mass spectrometers produces an astonishing amount of high-quality data in a brief period of time, leading to inevitable data analysis bottlenecks. Automated data analysis algorithms are required for rapid and repeatable processing of mass spectra containing hundreds of peaks, the part of the spectra containing information. New data processing algorithms must work with minimal user input, both to save operator time and to eliminate inevitable operator bias. Toward this end an accurate mathematical algorithm is presented that automatically locates and calculates the area beneath peaks. The promising numerical performance of this algorithm applied to raw data is presented. Published by Elsevier Ltd

• Type: Journal
• Year: 2005
• Where: APPML
• Authors: Anthony J. Kearsley, William E. Wallace, Javier Bernal, Charles M. Guttman
• Keywords: Algorithm, APPML 2005, Inevitable Data, Inevitable Operator Bias