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An efficient approach for compound identification based on the frequency features of mass spectra.
- Source :
-
Chemometrics & Intelligent Laboratory Systems . Mar2015, Vol. 142, p117-123. 7p. - Publication Year :
- 2015
-
Abstract
- Similarity-measure-based spectrum matching is an effective approach to chemical compound identification. When the sizes of both the query library and the reference library become increasingly large, most existing spectrum-matching methods encounter a seriously heavy computation burden. In this paper, an effective and efficient compound-identification approach is proposed based on the frequency features of mass spectra. Considering the sparsity of mass spectra, a nonzero feature-selection strategy is proposed to decrease the feature dimensionality of mass spectra. To further improve its efficiency, a correlation-based filtering strategy is presented to select the most correlated reference spectra in order to create a reduced reference library. Based on the decreased features and the reduced reference library, the frequency-feature-based composite similarity measures are computed to estimate the chemical abstracts service (CAS) registry numbers of the mass spectra blue in a query library. Due to the reduction in both the feature dimensionality and the reference library, the computation time of the proposed method is only about 6%–11% of that of the existing methods, while the identification performance remains sufficiently competitive. Experimental results demonstrate the feasibility and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01697439
- Volume :
- 142
- Database :
- Academic Search Index
- Journal :
- Chemometrics & Intelligent Laboratory Systems
- Publication Type :
- Academic Journal
- Accession number :
- 101918305
- Full Text :
- https://doi.org/10.1016/j.chemolab.2015.01.019