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Bottlenecks in advancing and applying multiomic data integration—common data resources as rate-limiting drivers

2025-10-10Artigo científico Acesso aberto
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dc.contributor.authorWettinger, Stephanie Bezzina
dc.contributor.authorKaraduzovic-Hadziabdic, Kanita
dc.contributor.authorAttard, Ritienne
dc.contributor.authorFarrugia, Rosienne
dc.contributor.authorWolford, Brooke N.
dc.contributor.authorChierici, Marco
dc.contributor.authorJurman, Giuseppe
dc.contributor.authorAlexiou, Panagiotis
dc.contributor.authorPeñalvo, José L.
dc.contributor.authorCosta, Rafael S.
dc.contributor.authorBasílio, José
dc.contributor.authorSabovcik, Frantisek
dc.contributor.authorVitorino, Rui
dc.contributor.authorSchmid, Johannes A.
dc.contributor.authorShigdel, Rajesh
dc.contributor.authorVilne, Baiba
dc.contributor.authorHatzigeorgiou, Artemis G.
dc.contributor.authorSopic, Miron
dc.contributor.authorDevaux, Yvan
dc.contributor.authorMagni, Paolo
dc.contributor.authorTellez-Plaza, Maria
dc.contributor.authorKreil, David P.
dc.contributor.authorGruca, Aleksandra
dc.contributor.institutionLAQV@REQUIMTE
dc.contributor.institutionDQ - Departamento de Química
dc.contributor.pblOxford University Press
dc.date.accessioned2026-02-05T18:01:01Z
dc.date.available2026-02-05T18:01:01Z
dc.date.issued2025-10-10
dc.description.abstractDespite striking successes in identifying novel biomarkers for improved patient stratification and predicting disease progression, numerous challenges remain in the effective integration and exploitation of multiomic data in biomedical applications beyond cancer, for which most bioinformatics strategies are developed and validated. That focus on cancer severely limits the effective development and advancement of algorithms in machine learning and artificial intelligence that do not suffer degraded out-of-domain performance. Generalizability and interpretability of models, however, are also required for robust insights that may translate into clinical practice. Work across different independent datasets is critical for establishing models robust towards unwanted variation in assays, protocols, and cohort populations. Disease-specific context like ethnicity, socioeconomic background, sex, lifestyle, disease phase, and tissue type also strongly affect molecular profiles. We here discuss atherosclerotic cardiovascular disease (ASCVD) as a high-impact non-cancer use case for the challenges remaining in the development and application of the latest bioinformatics approaches to multiomics data integration. ASCVD remains the leading cause of death globally. Disease aetiology, progression, and therapy outcome depend on a complex interplay of genetic, environmental, and lifestyle factors. Integrating these diverse data types effectively remains a challenge but holds transformative potential for personalized medicine. Discovery and access to data of sufficient diversity and extent form key bottlenecks. We here compile a first comprehensive overview of key data sets in ASCVD to complement the established cancer-focused resources as a foundation for future effective development and application of state-of-the-art bioinformatics tools for multiomic data integration.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent22
dc.format.extent1441827
dc.identifier.doi10.1093/bib/bbaf526
dc.identifier.issn1467-5463
dc.identifier.otherPURE: 132111558
dc.identifier.otherPURE UUID: 1dd80240-670b-4d3e-b67c-fc909f76d5ac
dc.identifier.otherPubMed: 41071609
dc.identifier.otherPubMedCentral: PMC12513167
dc.identifier.otherWOS: 001590649100001
dc.identifier.otherScopus: 105018397938
dc.identifier.urihttp://hdl.handle.net/10362/200081
dc.identifier.urlhttps://www.scopus.com/pages/publications/105018397938
dc.identifier.urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:001590649100001
dc.language.isoeng
dc.peerreviewedyes
dc.subjectmultiomic data integration
dc.subjectalgorithm generalizability
dc.subjectdata diversity
dc.subjectcommon data resources
dc.subjectatherosclerotic cardiovascular disease (ASCDV)
dc.subjectSDG 3 - Good Health and Well-being
dc.titleBottlenecks in advancing and applying multiomic data integration—common data resources as rate-limiting driversen
dc.title.subtitlethe high-impact use case of atherosclerotic cardiovascular diseaseen
dc.typejournal article
degois.publication.firstPage1
degois.publication.issue5
degois.publication.lastPage22
degois.publication.titleBriefings in Bioinformatics
degois.publication.volume26
dspace.entity.typePublication
rcaap.rightsopenAccess

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