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This repository contains the data used in [1] to evaluate the performance for metabolite identification from tandem mass spectra. These data have been extracted and processed in [2]. We used a subset of 4138 MS/MS spectra extracted from the GNPS public spectral library (https://gnps.ucsd.edu/ProteoSAFe/libraries.jsp) for training and evaluation. For searching, we used molecular structures from PubChem as candidate sets. Please mention and cite GNPS when using these data. The implementation of the method proposed in [1] is available on: https://version.aalto.fi/gitlab/kepaco/Fast-metabolite-identification-with-IOKR Files description: spectra.txt: informations about the MS/MS spectra (GNPS identifier, compound name and INCHI identifier) data_GNPS.mat: contains the molecular fingerprints, molecular formula and InCHI corresponding to the MS/MS spectra cv_ind.txt: indices of the cross-validation folds ind_eval.txt: indices of the examples used for evaluation candidates: fingerprints and INCHI for the different candidate sets input_kernels: contains 24 input kernel matrices References: [1] Brouard, C., Shen, H., Dührkop, K., d'Alché-Buc, F., Böcker, S. and Rousu, J.: Fast metabolite identification with Input Output Kernel Regression. In the proceedings of ISMB 2016, Bioinformatics 32(12): i28-i36, 2016. DOI: https://doi.org/10.1093/bioinformatics/btw246 [2] Dührkop, K., Shen, H., Meusel, M., Rousu, J. and Böcker, S.: Searching molecular structure databases with tandem mass spectra using CSI:FingerID. PNAS, 112(41), 12580-12585, 2015. doi:10.1073/pnas.1509788112
FOS: Computer and information sciences, Mass spectrometry, Structured prediction, Bioinformatics, Machine learning, Metabolomics, Metabolite identification
FOS: Computer and information sciences, Mass spectrometry, Structured prediction, Bioinformatics, Machine learning, Metabolomics, Metabolite identification
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