bioRxiv preprint doi: https://doi.org/10.1101/397760; this version posted August 22, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. A 3-fold kernel approach for characterizing Late Onset Alzheimer’s Disease Margherita Squillarioa,*, Federico Tomasia, Veronica Tozzoa, Annalisa Barlaa and Daniela Ubertib “for the Alzheimer’s Disease Neuroimaging Initiative**” aDIBRIS, University of Genoa, Via Dodecaneso 35, I-16146 Genova, Italy. E-mail address: {squillario, federico.tomasi, veronica.tozzo}@dibris.unige.it,
[email protected] bDepartment of Molecular and Translational Medicine, University of Brescia, Viale Europa 11, 25123, Brescia, Italy. E-mail address:
[email protected] * Corresponding author and Lead Contact. Tel: +39-010-353-6707; Fax: +39-010-353- 6699. ** Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp- content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf 1 bioRxiv preprint doi: https://doi.org/10.1101/397760; this version posted August 22, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.