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Random forest modelling demonstrates microglial and protein misfolding features to be key phenotypic markers in C9orf72-ALS

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dc.contributor.authorRifai, Olivia M.
dc.contributor.authorLongden, James
dc.contributor.authorO'Shaughnessy, Judi
dc.contributor.authorSewell, Michael D.E.
dc.contributor.authorPate, Judith
dc.contributor.authorMcDade, Karina
dc.contributor.authorDaniels, Michael J.D.
dc.contributor.authorAbrahams, Sharon
dc.contributor.authorChandran, Siddharthan
dc.contributor.authorMcColl, Barry W.
dc.contributor.authorSibley, Christopher R.
dc.contributor.authorGregory, Jenna M.
dc.contributor.institutionUniversity of Aberdeen.Medical Sciencesen
dc.contributor.institutionUniversity of Aberdeen.Neuroscienceen
dc.date.accessioned2023-06-21T08:52:00Z
dc.date.available2023-06-21T08:52:00Z
dc.date.issued2022-12
dc.descriptionAcknowledgments We gratefully acknowledge Professor Tom Gillingwater for his helpful comments and support. This work would not have been possible without the resources of the Edinburgh Brain Bank, and the people with ALS and their families who have generously donated tissue. This research was funded in part by a studentship from the Wellcome Trust (108890/Z/15/Z) to OMR and MDES, a Pathological Society and Jean Shanks foundation grant (217CHA R46564) to JMG and JO, and a Sir Henry Dale fellowship jointly funded by the Wellcome Trust and the Royal Society (215454/Z/19/Z) to CRS.en
dc.description.statusPeer revieweden
dc.format.extent16
dc.format.extent25542426
dc.identifier219653261
dc.identifier50e18409-8db0-4a78-b3f0-449c73eec28a
dc.identifier85139709721
dc.identifier.citationRifai, O M, Longden, J, O'Shaughnessy, J, Sewell, M D E, Pate, J, McDade, K, Daniels, M J D, Abrahams, S, Chandran, S, McColl, B W, Sibley, C R & Gregory, J M 2022, 'Random forest modelling demonstrates microglial and protein misfolding features to be key phenotypic markers in C9orf72-ALS', The Journal of pathology, vol. 258, no. 4, pp. 366-381. https://doi.org/10.1002/path.6008en
dc.identifier.doi10.1002/path.6008
dc.identifier.iss4en
dc.identifier.issn0022-3417
dc.identifier.otherBibtex: https://doi.org/10.1002/path.6008
dc.identifier.otherORCID: /0000-0003-3337-4079/work/122953770
dc.identifier.urihttps://hdl.handle.net/2164/20950
dc.identifier.urlhttps://onlinelibrary.wiley.com/doi/abs/10.1002/path.6008en
dc.identifier.vol258en
dc.language.isoeng
dc.relation.ispartofThe Journal of pathologyen
dc.subjectAmyotrophic lateral sclerosisen
dc.subjectfrontotemporal dementiaen
dc.subjectC9orf72en
dc.subjectneuroinflammationen
dc.subjectmicrogliaen
dc.subjectpost-mortem tissueen
dc.subjectTDP-43en
dc.subjectFUSen
dc.subjectmachine learningen
dc.subjectdigital pathologyen
dc.subjectRB Pathologyen
dc.subjectWellcome Trusten
dc.subject108890/Z/15/Zen
dc.subjectOtheren
dc.subject215454/Z/19/Zen
dc.subjectSupplementary Informationen
dc.subject.lccRBen
dc.titleRandom forest modelling demonstrates microglial and protein misfolding features to be key phenotypic markers in C9orf72-ALSen
dc.typeJournal articleen

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