<p>Identifying imaging genetic associations via regional morphometricity estimation</p>

Jingxuan Bao; Zixuan Wen; Mansu Kim; Andrew J. Saykin; Paul M. Thompson; Yize Zhao; Li Shen; for the Alzheimer’s Disease Neuroimaging Initiative

doi:10.7490/f1000research.1118808.1

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Bao J, Wen Z, Kim M et al. Identifying imaging genetic associations via regional morphometricity estimation [version 1; not peer reviewed]. F1000Research 2021, 10:999 (poster) (https://doi.org/10.7490/f1000research.1118808.1)

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Identifying imaging genetic associations via regional morphometricity estimation

Jingxuan Bao, Zixuan Wen, Mansu Kim, Andrew J. Saykin, Paul M. Thompson, Yize Zhao, Li Shen¹, for the Alzheimer’s Disease Neuroimaging Initiative

Published 02 Oct 2021 (https://doi.org/10.7490/f1000research.1118808.1)

Author Affiliations

¹ University of Pennsylvania, USA

Copyright © 2021 Bao J et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Published 02 Oct 2021

Identifying imaging genetic associations via regional morphometricity estimation
[version 1; not peer reviewed]

Jingxuan Bao, Zixuan Wen, Mansu Kim, Andrew J. Saykin, Paul M. Thompson, Yize Zhao, Li Shen¹, for the Alzheimer’s Disease Neuroimaging Initiative

Author Affiliations

¹ University of Pennsylvania, USA

Presented at

Pacific Symposium on Biocomputing (PSB) 2022

Abstract

Competing Interests

No competing interests were disclosed

Keywords

Brain imaging genetics, Regional morphometricity, Alzheimer's Disease

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