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Challenges and opportunities for statistics in Omics data analysis

2026-04Capítulo de livro Acesso embargado
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datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorCarrasquinha, Eunice
dc.contributor.authorSousa, Lisete
dc.contributor.authorSilva, Carina
dc.contributor.editorGama-Carvalho, Margarida
dc.contributor.editorFigueiredo, Andreia
dc.contributor.editorPinto, Francisco Rodrigues
dc.date.accessioned2026-05-26T16:00:46Z
dc.date.available2026-05-26T16:00:46Z
dc.date.issued2026-04
dc.description.abstractOmics data, comprising a diverse array of high-throughput molecular datasets, present substantial statistical challenges due to their intrinsic heterogeneity and variability. Effectively distinguishing biologically meaningful variations from random noise requires the application and development of robust statistical approaches. Interdisciplinary collaboration plays a pivotal role in refining these methodologies and enhancing the understanding of intricate biological systems. This chapter reviews the importance of statistical methods in omics data analysis, highlighting the need for ongoing advancements to address key challenges, including experimental design, preprocessing, dimensionality reduction, statistical modeling of complex datasets, and the interpretation of results. The pursuit of improved reliability in biological insights creates opportunities for the development and refinement of advanced statistical methodologies.eng
dc.identifier.citationCarrasquinha E, Sousa L, Silva C. Challenges and opportunities for statistics in Omics data analysis. In: Gama-Carvalho M, Figueiredo A, Pinto RP, editors. Omics approaches in biomedicine and biotechnology: from technologies to data to biological knowledge. Springer; 2026. p. 205-24.
dc.identifier.doi10.1007/978-3-032-18966-0_10
dc.identifier.isbn9783032189653
dc.identifier.isbn9783032189660
dc.identifier.issn0065-2598
dc.identifier.issn2214-8019
dc.identifier.urihttp://hdl.handle.net/10400.21/22903
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature Switzerland
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-032-18966-0_10
dc.relation.ispartofAdvances in Experimental Medicine and Biology
dc.relation.ispartofOmics Approaches in Biomedicine and Biotechnology
dc.relation.ispartofseriesAdvances in Experimental Medicine and Biology
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectStatistics
dc.subjectOmics
dc.subjectHigh-dimensional data
dc.subjectExperimental design
dc.subjectMachine learning
dc.titleChallenges and opportunities for statistics in Omics data analysiseng
dc.typebook part
dspace.entity.typePublication
oaire.citation.endPage224
oaire.citation.startPage205
oaire.citation.titleOmics approaches in biomedicine and biotechnology: from technologies to data to biological knowledge
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameSilva
person.givenNameCarina
person.identifier.ciencia-id2411-5936-0820
person.identifier.orcid0000-0003-1021-7935
person.identifier.scopus-author-id55258764900
relation.isAuthorOfPublication81a5cd80-1982-43ba-bde5-4c43ae0e5234
relation.isAuthorOfPublication.latestForDiscovery81a5cd80-1982-43ba-bde5-4c43ae0e5234

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