dc.contributor.author | Rifai, Olivia M. | |
dc.contributor.author | Longden, James | |
dc.contributor.author | O’Shaughnessy, Judi | |
dc.contributor.author | Sewell, Michael D.E. | |
dc.contributor.author | McDade, Karina | |
dc.contributor.author | Daniels, Michael J.D. | |
dc.contributor.author | Abrahams, Sharon | |
dc.contributor.author | Chandran, Siddharthan | |
dc.contributor.author | McColl, Barry | |
dc.contributor.author | Sibley, Christopher R. | |
dc.contributor.author | Gregory, Jenna M. | |
dc.date.accessioned | 2022-08-01T10:05:01Z | |
dc.date.available | 2022-08-01T10:05:01Z | |
dc.date.issued | 2021-12-10 | |
dc.identifier | 218810196 | |
dc.identifier | 9f114434-3249-428e-ba21-900e99d0c97f | |
dc.identifier.citation | Rifai , O M , Longden , J , O’Shaughnessy , J , Sewell , M D E , McDade , K , Daniels , M J D , Abrahams , S , Chandran , S , McColl , B , Sibley , C R & Gregory , J M 2021 , ' Random forest modelling of neuropathological features identifies microglial activation as an accurate pathological classifier of C9orf72-related amyotrophic lateral sclerosis ' , bioRxiv . https://doi.org/10.1101/2021.12.10.471808 | en |
dc.identifier.other | ORCID: /0000-0003-3337-4079/work/113328250 | |
dc.identifier.other | Bibtex: Rifai2021.12.10.471808 | |
dc.identifier.uri | https://hdl.handle.net/2164/18977 | |
dc.description | Acknowledgments 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. We gratefully acknowledge Dr. Tom Gillingwater for his helpful comments and support. This work would also not be possible without the resources of the Edinburgh Brain Bank. The authors declare no conflicts of interest. SD numbers of cases from the Edinburgh Brain Bank included in the study are available upon request. | en |
dc.format.extent | 5102435 | |
dc.language.iso | eng | |
dc.relation.ispartof | bioRxiv | en |
dc.subject | Amyotrophic lateral sclerosis | en |
dc.subject | frontotemporal dementia | en |
dc.subject | C9orf72 | en |
dc.subject | neuroinflammation | en |
dc.subject | microglia | en |
dc.subject | post-mortem tissue | en |
dc.subject | RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry | en |
dc.subject | Wellcome Trust | en |
dc.subject | 108890/Z/15/Z | en |
dc.subject | 215454/Z/19/Z | en |
dc.subject.lcc | RC0321 | en |
dc.title | Random forest modelling of neuropathological features identifies microglial activation as an accurate pathological classifier of C9orf72-related amyotrophic lateral sclerosis | en |
dc.type | Journal article | en |
dc.contributor.institution | University of Aberdeen.Medical Sciences | en |
dc.contributor.institution | University of Aberdeen.Neuroscience | en |
dc.description.status | Non peer reviewed | en |
dc.identifier.doi | https://doi.org/10.1101/2021.12.10.471808 | |