Data analysis in applications of chromatography coupled with mass spectrometry and ion mobility spectrometry

This chapter explores the data processing methodologies essential for leveraging the synergy between chromatography, mass spectrometry (MS), and ion mobility spectrometry (IMS) in analytical applications. In this overview, we encompass the entire processing pipeline, starting from the acquisition an...

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Autores: Pérez-López, Carlos, Jaumot, Joaquim, Puig-Castellví, Francesc
Tipo de recurso: otro
Estado:Versión aceptada para publicación
Fecha de publicación:2026
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/418822
Acceso en línea:http://hdl.handle.net/10261/418822
https://api.elsevier.com/content/abstract/scopus_id/105029204514
Access Level:acceso embargado
Palabra clave:Multivariate analysis
Data processing
Feature extraction
Hyphenated techniques
Ion mobility
Mass spectrometry
http://metadata.un.org/sdg/12
http://metadata.un.org/sdg/9
http://metadata.un.org/sdg/6
http://metadata.un.org/sdg/3
Ensure healthy lives and promote well-being for all at all ages
Ensure availability and sustainable management of water and sanitation for all
Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Ensure sustainable consumption and production patterns
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spelling Data analysis in applications of chromatography coupled with mass spectrometry and ion mobility spectrometryPérez-López, CarlosJaumot, JoaquimPuig-Castellví, FrancescMultivariate analysisData processingFeature extractionHyphenated techniquesIon mobilityMass spectrometryhttp://metadata.un.org/sdg/12http://metadata.un.org/sdg/9http://metadata.un.org/sdg/6http://metadata.un.org/sdg/3Ensure healthy lives and promote well-being for all at all agesEnsure availability and sustainable management of water and sanitation for allBuild resilient infrastructure, promote inclusive and sustainable industrialization and foster innovationEnsure sustainable consumption and production patternsThis chapter explores the data processing methodologies essential for leveraging the synergy between chromatography, mass spectrometry (MS), and ion mobility spectrometry (IMS) in analytical applications. In this overview, we encompass the entire processing pipeline, starting from the acquisition and management of raw data generated by these hyphenated techniques, through to the final stages of quantitation and annotation. We concentrate on delineating the challenges posed by complex datasets and the methodologies employed for feature extraction, followed by their multivariate analysis. Moreover, the chapter explores diverse approaches for annotating unknown compounds, exploiting the latest advancements in the field, and capitalizing on the complementary information offered by MS and IMS. Case studies exemplifying the application of these techniques in various analytical domains underscore their efficacy in enhancing sensitivity, selectivity, and overall analytical performance. This comprehensive overview serves as a valuable resource for researchers and practitioners seeking to harness the full potential of hyphenated chromatography with MS and IMS for data-driven insights in analytical chemistry.Peer reviewedElsevierConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202620262026info:eu-repo/semantics/otherhttp://purl.org/coar/resource_type/c_3248Postprintinfo:eu-repo/semantics/acceptedVersioninfo:eu-repo/semantics/bookParthttp://hdl.handle.net/10261/418822https://api.elsevier.com/content/abstract/scopus_id/105029204514reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésProblem Oriented Analytical Chemistry Driven by Chemometricsttps://doi.org/10.1016/B978-0-443-22163-7.00018-8Síinfo:eu-repo/semantics/embargoedAccessoai:digital.csic.es:10261/4188222026-05-22T06:33:51Z
dc.title.none.fl_str_mv Data analysis in applications of chromatography coupled with mass spectrometry and ion mobility spectrometry
title Data analysis in applications of chromatography coupled with mass spectrometry and ion mobility spectrometry
spellingShingle Data analysis in applications of chromatography coupled with mass spectrometry and ion mobility spectrometry
Pérez-López, Carlos
Multivariate analysis
Data processing
Feature extraction
Hyphenated techniques
Ion mobility
Mass spectrometry
http://metadata.un.org/sdg/12
http://metadata.un.org/sdg/9
http://metadata.un.org/sdg/6
http://metadata.un.org/sdg/3
Ensure healthy lives and promote well-being for all at all ages
Ensure availability and sustainable management of water and sanitation for all
Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Ensure sustainable consumption and production patterns
title_short Data analysis in applications of chromatography coupled with mass spectrometry and ion mobility spectrometry
title_full Data analysis in applications of chromatography coupled with mass spectrometry and ion mobility spectrometry
title_fullStr Data analysis in applications of chromatography coupled with mass spectrometry and ion mobility spectrometry
title_full_unstemmed Data analysis in applications of chromatography coupled with mass spectrometry and ion mobility spectrometry
title_sort Data analysis in applications of chromatography coupled with mass spectrometry and ion mobility spectrometry
dc.creator.none.fl_str_mv Pérez-López, Carlos
Jaumot, Joaquim
Puig-Castellví, Francesc
author Pérez-López, Carlos
author_facet Pérez-López, Carlos
Jaumot, Joaquim
Puig-Castellví, Francesc
author_role author
author2 Jaumot, Joaquim
Puig-Castellví, Francesc
author2_role author
author
dc.contributor.none.fl_str_mv Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Multivariate analysis
Data processing
Feature extraction
Hyphenated techniques
Ion mobility
Mass spectrometry
http://metadata.un.org/sdg/12
http://metadata.un.org/sdg/9
http://metadata.un.org/sdg/6
http://metadata.un.org/sdg/3
Ensure healthy lives and promote well-being for all at all ages
Ensure availability and sustainable management of water and sanitation for all
Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Ensure sustainable consumption and production patterns
topic Multivariate analysis
Data processing
Feature extraction
Hyphenated techniques
Ion mobility
Mass spectrometry
http://metadata.un.org/sdg/12
http://metadata.un.org/sdg/9
http://metadata.un.org/sdg/6
http://metadata.un.org/sdg/3
Ensure healthy lives and promote well-being for all at all ages
Ensure availability and sustainable management of water and sanitation for all
Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Ensure sustainable consumption and production patterns
description This chapter explores the data processing methodologies essential for leveraging the synergy between chromatography, mass spectrometry (MS), and ion mobility spectrometry (IMS) in analytical applications. In this overview, we encompass the entire processing pipeline, starting from the acquisition and management of raw data generated by these hyphenated techniques, through to the final stages of quantitation and annotation. We concentrate on delineating the challenges posed by complex datasets and the methodologies employed for feature extraction, followed by their multivariate analysis. Moreover, the chapter explores diverse approaches for annotating unknown compounds, exploiting the latest advancements in the field, and capitalizing on the complementary information offered by MS and IMS. Case studies exemplifying the application of these techniques in various analytical domains underscore their efficacy in enhancing sensitivity, selectivity, and overall analytical performance. This comprehensive overview serves as a valuable resource for researchers and practitioners seeking to harness the full potential of hyphenated chromatography with MS and IMS for data-driven insights in analytical chemistry.
publishDate 2026
dc.date.none.fl_str_mv 2026
2026
2026
dc.type.none.fl_str_mv info:eu-repo/semantics/other
http://purl.org/coar/resource_type/c_3248
Postprint
info:eu-repo/semantics/acceptedVersion
dc.type.openaire.fl_str_mv info:eu-repo/semantics/bookPart
format other
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/418822
https://api.elsevier.com/content/abstract/scopus_id/105029204514
url http://hdl.handle.net/10261/418822
https://api.elsevier.com/content/abstract/scopus_id/105029204514
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Problem Oriented Analytical Chemistry Driven by Chemometrics
ttps://doi.org/10.1016/B978-0-443-22163-7.00018-8
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/embargoedAccess
eu_rights_str_mv embargoedAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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