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dc.contributor.authorVafaee, Fatemehen_US
dc.contributor.authorDiakos, Connieen_US
dc.contributor.authorKirschner, Michaela Ben_US
dc.contributor.authorReid, Glenen_US
dc.contributor.authorMichael, Michael Zenonen_US
dc.contributor.authorHorvath, Lisa Gen_US
dc.contributor.authorAlinejad-Rokny, Hamiden_US
dc.contributor.authorCheng, Zhangkai Jasonen_US
dc.contributor.authorKuncic, Zdenkaen_US
dc.contributor.authorClarke, Stevenen_US
dc.date.accessioned2019-03-13T23:24:59Z
dc.date.available2019-03-13T23:24:59Z
dc.date.issued2018-06-01
dc.identifier.citationVafaee, F., Diakos, C., Kirschner, M. B., Reid, G., Michael, M. Z., Horvath, L. G., … Clarke, S. (2018). A data-driven, knowledge-based approach to biomarker discovery: application to circulating microRNA markers of colorectal cancer prognosis. Npj Systems Biology and Applications, 4(1). https://doi.org/10.1038/s41540-018-0056-1en_US
dc.identifier.issn2056-7189
dc.identifier.urihttp://hdl.handle.net/2328/39101
dc.description© The Author(s) 2018. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.description.abstractRecent advances in high-throughput technologies have provided an unprecedented opportunity to identify molecular markers of disease processes. This plethora of complex-omics data has simultaneously complicated the problem of extracting meaningful molecular signatures and opened up new opportunities for more sophisticated integrative and holistic approaches. In this era, effective integration of data-driven and knowledge-based approaches for biomarker identification has been recognised as key to improving the identification of high-performance biomarkers, and necessary for translational applications. Here, we have evaluated the role of circulating microRNA as a means of predicting the prognosis of patients with colorectal cancer, which is the second leading cause of cancer-related death worldwide. We have developed a multi-objective optimisation method that effectively integrates a data-driven approach with the knowledge obtained from the microRNA-mediated regulatory network to identify robust plasma microRNA signatures which are reliable in terms of predictive power as well as functional relevance. The proposed multi-objective framework has the capacity to adjust for conflicting biomarker objectives and to incorporate heterogeneous information facilitating systems approaches to biomarker discovery. We have found a prognostic signature of colorectal cancer comprising 11 circulating microRNAs. The identified signature predicts the patients’ survival outcome and targets pathways underlying colorectal cancer progression. The altered expression of the identified microRNAs was confirmed in an independent public data set of plasma samples of patients in early stage vs advanced colorectal cancer. Furthermore, the generality of the proposed method was demonstrated across three publicly available miRNA data sets associated with biomarker studies in other diseases.en_US
dc.language.isoenen_US
dc.publisherSpringer Nature Publishing AGen_US
dc.rights© The Author(s) 2018en_US
dc.subjectBiochemical networksen_US
dc.subjectBiomarkersen_US
dc.titleA data-driven, knowledge-based approach to biomarker discovery: application to circulating microRNA markers of colorectal cancer prognosisen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1038/s41540-018-0056-1en_US
dc.rights.holderThe Author(s)en_US
dc.rights.licenseCC-BY
local.contributor.authorOrcidLookupVafaee, Fatemeh: https://orcid.org/0000-0002-7521-2417
local.contributor.authorOrcidLookupKirschner, Michaela B: https://orcid.org/0000-0001-7444-9829
local.contributor.authorOrcidLookupMichael, Michael Zenon: https://orcid.org/0000-0001-5954-7105
local.contributor.authorOrcidLookupKuncic, Zdenka: https://orcid.org/0000-0001-6765-3215


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