Combine multiple mass spectral similarity measures for compound identification
by Jun Zhang; Yi Xia; Chun-Hou Zheng; Bing Wang; Xiang Zhang; Peng Chen
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 15, No. 1, 2016

Abstract: Compound identification in gas chromatography-mass spectrometry (GC-MS) is usually achieved by comparing a query mass spectrum with reference spectral library. The rapid growing spectral library requires a more powerful spectral similarity measure to achieve the best identification performance. In this study, seven spectrum similarity measures were combined to improve the identification accuracy. To reduce the computation time, absolute value distance (ABS_VD) similarity measure was chosen to construct a sub-library to be searched by all similarity measures. Particle Swarm Optimisation (PSO) algorithm was used to first find the optimised weights for the similarity score of each similarity measure based on the training data, and then the optimised weights were applied to the test data. Simulation study using the NIST/EPA/NIH Mass Spectral Library 2005 indicates that the combination of multiple similarity measures achieves a better performance than any single similarity measure, with the identification accuracy improved by 2.2% and 1.7% for the training data and the test data, respectively.

Online publication date: Thu, 21-Apr-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Mining and Bioinformatics (IJDMB):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com