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RISS 인기검색어
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- 저자 : ( Ekaterina V. Ostrovidova ) (검색결과 3 건)
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Boris L. Milman,Ekaterina V. Ostrovidova,Inna K. Zhurkovich 사단법인 한국질량분석학회 2019 Mass spectrometry letters Vol.10 No.3
Algorithms and software for predicting tandem mass spectra have been developed in recent years. In this work, we explore how distinct in silico MS 2 spectra are predicted for isomers, i.e. compounds having the same formula and similar molec-ular structures, to differentiate between them. We used the CFM-ID 2.0/3.0 predictor with regard to (a) test compounds, whose experimental mass spectra had been randomly sampled from the MassBank of North America (MoNA) collection, and to (b) the most widespread isomers of test compounds searched in the PubChem database. In the first validation test, in silico mass spectra constitute a reference library, and library searches are performed for test experimental spectra of “unknowns”. The searches led to the true positive rate (TPR) of (46-48 ± 10)%. In the second test, in silico and experimental spectra were interchanged and this resulted in a TPR of (58 ± 10)%. There were no significant differences between results obtained with different metrics of spectral similarity and predictor versions. In a comparison of test compounds vs. their isomers, a statistically significant correlation between mass spectral data and structural features was observed. The TPR values obtained should be regarded as reasonable results for predicting tandem mass spectra of related chemical structures.
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Milman, Boris L.,Ostrovidova, Ekaterina V.,Zhurkovich, Inna K. Korean Society for Mass Spectrometry 2019 Mass spectrometry letters Vol.10 No.3
Algorithms and software for predicting tandem mass spectra have been developed in recent years. In this work, we explore how distinct in silico $MS^2$ spectra are predicted for isomers, i.e. compounds having the same formula and similar molecular structures, to differentiate between them. We used the CFM-ID 2.0/3.0 predictor with regard to (a) test compounds, whose experimental mass spectra had been randomly sampled from the MassBank of North America (MoNA) collection, and to (b) the most widespread isomers of test compounds searched in the PubChem database. In the first validation test, in silico mass spectra constitute a reference library, and library searches are performed for test experimental spectra of "unknowns". The searches led to the true positive rate (TPR) of ($46-48{\pm}10$)%. In the second test, in silico and experimental spectra were interchanged and this resulted in a TPR of ($58{\pm}10$)%. There were no significant differences between results obtained with different metrics of spectral similarity and predictor versions. In a comparison of test compounds vs. their isomers, a statistically significant correlation between mass spectral data and structural features was observed. The TPR values obtained should be regarded as reasonable results for predicting tandem mass spectra of related chemical structures.
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( Boris L. Milman ),( Ekaterina V. Ostrovidova ),( Inna K. Zhurkovich ) 한국질량분석학회 2019 Mass spectrometry letters Vol.10 No.3
Algorithms and software for predicting tandem mass spectra have been developed in recent years. In this work, we explore how distinct in silico MS<sup>2</sup> spectra are predicted for isomers, i.e. compounds having the same formula and similar molecular structures, to differentiate between them. We used the CFM-ID 2.0/3.0 predictor with regard to (a) test compounds, whose experimental mass spectra had been randomly sampled from the MassBank of North America (MoNA) collection, and to (b) the most widespread isomers of test compounds searched in the PubChem database. In the first validation test, in silico mass spectra constitute a reference library, and library searches are performed for test experimental spectra of “unknowns”. The searches led to the true positive rate (TPR) of (46-48 ± 10)%. In the second test, in silico and experimental spectra were interchanged and this resulted in a TPR of (58 ± 10)%. There were no significant differences between results obtained with different metrics of spectral similarity and predictor versions. In a comparison of test compounds vs. their isomers, a statistically significant correlation between mass spectral data and structural features was observed. The TPR values obtained should be regarded as reasonable results for predicting tandem mass spectra of related chemical structures.
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