Improved optimization of the FT-ICR MS phase correction function using a genetic algorithm

David Kilgour, Mark James Neal, Andrew J. Soulby, Peter O'Connor

Research output: Contribution to journalArticlepeer-review

24 Citations (SciVal)

Abstract

RATIONALE Fourier Transform Ion Cyclotron Resonance mass spectra exhibit improved resolving power, mass accuracy and signal-to-noise ratio when presented in absorption mode; a process which requires calculation of a phase correction function. Mass spectrometric images can contain many thousands of pixels, hence methods of decreasing the time required to solve for a phase correction function will result in significant improvements in this application.

METHODS A genetic algorithm approach for optimizing the phase correction function has been developed and compared to a previously described convergent iteration technique.

RESULTS The genetic algorithm method has been shown to offer a five-fold improvement in processing speed compared to the previous iterative approach used in the Autophaser algorithm, whilst maintaining the levels of accuracy. This translates to an 11 hour improvement in processing for a 20 000 pixel mass spectrometric image.

CONCLUSIONS The genetic algorithm method described in this manuscript offers significant processing speed advantages over the previously described convergent iteration technique. This improvement is key to allowing the future routine use of absorption mode mass spectrometric images.
Original languageEnglish
Pages (from-to)1977-1982
Number of pages6
JournalRapid Communications in Mass Spectrometry
Volume27
Issue number17
Early online date31 Jul 2013
DOIs
Publication statusPublished - 15 Sept 2013

Keywords

  • Artificial intelligence

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