Status已發表Published
Classification based Integration of Quantifications for LC-MS Analysis
Li,Tianjun; Chen,Long; Wei,Huiqin
2018-12-01
Source Publication2018 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2018
Pages97-102
AbstractA classification based integration of quantification method for the Liquid Chromatography - Mass Spectrometry (LC-MS) analysis is described in this paper. Typically, one biological tissue may be sent to the LC-MS many times in practice to generate multiple LC-MS data. Due to the precise level or the profile of the search engine, these multiple individual quantitative results of the multiple LC-MS data may be partially identical. Here we proposed a method to integrate the quantitative results for the case where there are multiple individual measurements but the results are only partially identical. This proposed method applies a classifier to the peptides and treats the predicted probabilities of the classification as the weights to combine these multiple individual quantitative results into a better one. Experimental results show that in the task of quantitative LC-MS, the results generated by this integration method perform better than the ones produced by other individual measurements.
DOI10.1109/SPAC46244.2018.8965613
URLView the original
Language英語English
Scopus ID2-s2.0-85079175561
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversity of Macau,Department of Computer and Information Science,Taipa,Macao
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Li,Tianjun,Chen,Long,Wei,Huiqin. Classification based Integration of Quantifications for LC-MS Analysis[C], 2018, 97-102.
APA Li,Tianjun., Chen,Long., & Wei,Huiqin (2018). Classification based Integration of Quantifications for LC-MS Analysis. 2018 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2018, 97-102.
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