A mass spectra-based compound-identification approach with a reduced reference library

Authors:
Zhan-Li Sun;Kin-Man Lam;Jun Zhang
Affiliations:
School of Electrical Engineering and Automation, Anhui University, China;Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hong Kong;School of Electrical Engineering and Automation, Anhui University, China
Venue:
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
Year:
2013

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Abstract

In this paper, an effective and efficient compound identification approach is proposed based on the frequency feature of mass spectrum. A nonzero feature-retention strategy, and a correlation based-reference library reduction strategy, are designed in the proposed algorithm to reduce the computation burden. Further, a frequency feature based-composite similarity measure is adopted to decide the chemical abstracts service (CAS) registry numbers of mass spectral samples. Experimental results demonstrate the feasibility and efficiency of the proposed method.