Filter and Wrapper Stacking Ensemble (FWSE): A Robust Approach for Reliable Biomarker Discovery in High-Dimensional Omics Data

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aut.relation.issue6
aut.relation.journalBrief Bioinform
aut.relation.startpagebbad382
aut.relation.volume24
dc.contributor.authorBudhraja, Sugam
dc.contributor.authorDoborjeh, Maryam
dc.contributor.authorSingh, Balkaran
dc.contributor.authorTan, Samuel
dc.contributor.authorDoborjeh, Zohreh
dc.contributor.authorLai, Edmund
dc.contributor.authorMerkin, Alexander
dc.contributor.authorLee, Jimmy
dc.contributor.authorGoh, Wilson
dc.contributor.authorKasabov, Nikola
dc.date.accessioned2023-11-08T23:21:19Z
dc.date.available2023-11-08T23:21:19Z
dc.date.issued2023
dc.description.abstractSelecting informative features, such as accurate biomarkers for disease diagnosis, prognosis and response to treatment, is an essential task in the field of bioinformatics. Medical data often contain thousands of features and identifying potential biomarkers is challenging due to small number of samples in the data, method dependence and non-reproducibility. This paper proposes a novel ensemble feature selection method, named Filter and Wrapper Stacking Ensemble (FWSE), to identify reproducible biomarkers from high-dimensional omics data. In FWSE, filter feature selection methods are run on numerous subsets of the data to eliminate irrelevant features, and then wrapper feature selection methods are applied to rank the top features. The method was validated on four high-dimensional medical datasets related to mental illnesses and cancer. The results indicate that the features selected by FWSE are stable and statistically more significant than the ones obtained by existing methods while also demonstrating biological relevance. Furthermore, FWSE is a generic method, applicable to various high-dimensional datasets in the fields of machine intelligence and bioinformatics.
dc.identifier.citationBrief Bioinform, ISSN: 1477-4054 (Print); 1477-4054 (Online), Oxford University Press (OUP), 24(6), bbad382-. doi: 10.1093/bib/bbad382
dc.identifier.doi10.1093/bib/bbad382
dc.identifier.issn1477-4054
dc.identifier.issn1477-4054
dc.identifier.urihttp://hdl.handle.net/10292/16895
dc.languageeng
dc.publisherOxford University Press (OUP)
dc.relation.urihttps://academic.oup.com/bib/article/24/6/bbad382/7330499
dc.rights© The Author(s) 2023. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
dc.rights.accessrightsOpenAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectbiomarker discovery
dc.subjectensemble learning
dc.subjectfeature selection
dc.subjectgenomics
dc.subjecthigh-dimensional data
dc.subjectproteomics
dc.subjectbiomarker discovery
dc.subjectensemble learning
dc.subjectfeature selection
dc.subjectgenomics
dc.subjecthigh-dimensional data
dc.subjectproteomics
dc.subject0601 Biochemistry and Cell Biology
dc.subject0802 Computation Theory and Mathematics
dc.subject0899 Other Information and Computing Sciences
dc.subjectBioinformatics
dc.subject3101 Biochemistry and cell biology
dc.subject3102 Bioinformatics and computational biology
dc.subject3105 Genetics
dc.subject.meshAlgorithms
dc.subject.meshArtificial Intelligence
dc.subject.meshBiomarkers
dc.subject.meshHumans
dc.subject.meshMental Disorders
dc.subject.meshNeoplasms
dc.subject.meshHumans
dc.subject.meshAlgorithms
dc.subject.meshArtificial Intelligence
dc.subject.meshBiomarkers
dc.subject.meshNeoplasms
dc.subject.meshMental Disorders
dc.titleFilter and Wrapper Stacking Ensemble (FWSE): A Robust Approach for Reliable Biomarker Discovery in High-Dimensional Omics Data
dc.typeJournal Article
pubs.elements-id528015
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