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http://hdl.handle.net/2445/180153
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DC Field | Value | Language |
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dc.contributor.author | Madrid Gambín, Francisco Javier | - |
dc.contributor.author | Oller Moreno, Sergio | - |
dc.contributor.author | Fernandez, Luis | - |
dc.contributor.author | Bartova, Simona | - |
dc.contributor.author | Giner, Maria Pilar | - |
dc.contributor.author | Joyce, Christopher | - |
dc.contributor.author | Ferraro, Francesco | - |
dc.contributor.author | Montoliu, Ivan | - |
dc.contributor.author | Moco, Sofia | - |
dc.contributor.author | Marco Colás, Santiago | - |
dc.date.accessioned | 2021-09-20T17:09:44Z | - |
dc.date.available | 2021-09-20T17:09:44Z | - |
dc.date.issued | 2020-01-13 | - |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.uri | http://hdl.handle.net/2445/180153 | - |
dc.description.abstract | Nuclear magnetic resonance (NMR)-based metabolomics is widely used to obtain metabolic fingerprints of biological systems. While targeted workflows require previous knowledge of metabolites, prior to statistical analysis, untargeted approaches remain a challenge. Computational tools dealing with fully untargeted NMR-based metabolomics are still scarce or not user-friendly. Therefore, we developed AlpsNMR (Automated spectraL Processing System for NMR), an R package that provides automated and efficient signal processing for untargeted NMR metabolomics. AlpsNMR includes spectra loading, metadata handling, automated outlier detection, spectra alignment and peak-picking, integration and normalization. The resulting output can be used for further statistical analysis. AlpsNMR proved effective in detecting metabolite changes in a test case. The tool allows less experienced users to easily implement this workflow from spectra to a ready-to-use dataset in their routines. | - |
dc.format.extent | 3 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Oxford University Press | - |
dc.relation.isformatof | Versió postprint del document publicat a: https://doi.org/10.1093/bioinformatics/btaa022 | - |
dc.relation.ispartof | Bioinformatics, 2020, vol. 36, num. 9, p. 2943-2945 | - |
dc.relation.uri | https://doi.org/10.1093/bioinformatics/btaa022 | - |
dc.rights | (c) Madrid Gambín, Francisco Javier et al., 2020 | - |
dc.source | Articles publicats en revistes (Enginyeria Electrònica i Biomèdica) | - |
dc.subject.classification | Metabòlits | - |
dc.subject.classification | Ressonància magnètica nuclear | - |
dc.subject.classification | Programari | - |
dc.subject.other | Metabolites | - |
dc.subject.other | Nuclear magnetic resonance | - |
dc.subject.other | Computer software | - |
dc.title | Alpsnmr: an r package for signal processing of fully untargeted nmr-based metabolomics | - |
dc.type | info:eu-repo/semantics/article | - |
dc.type | info:eu-repo/semantics/acceptedVersion | - |
dc.identifier.idgrec | 699828 | - |
dc.date.updated | 2021-09-20T17:09:44Z | - |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
Appears in Collections: | Articles publicats en revistes (Enginyeria Electrònica i Biomèdica) |
Files in This Item:
File | Description | Size | Format | |
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699828.pdf | 1.02 MB | Adobe PDF | View/Open |
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