| Literature DB >> 27079753 |
Genevera I Allen1, Nicola Amoroso2, Catalina Anghel3, Venkat Balagurusamy4, Christopher J Bare5, Derek Beaton6, Roberto Bellotti2, David A Bennett7, Kevin L Boehme8, Paul C Boutros9, Laura Caberlotto10, Cristian Caloian3, Frederick Campbell1, Elias Chaibub Neto5, Yu-Chuan Chang11, Beibei Chen12, Chien-Yu Chen13, Ting-Ying Chien14, Tim Clark15, Sudeshna Das15, Christos Davatzikos16, Jieyao Deng17, Donna Dillenberger4, Richard J B Dobson18, Qilin Dong17, Jimit Doshi16, Denise Duma19, Rosangela Errico20, Guray Erus16, Evan Everett1, David W Fardo21, Stephen H Friend5, Holger Fröhlich22, Jessica Gan1, Peter St George-Hyslop23, Satrajit S Ghosh24, Enrico Glaab25, Robert C Green26, Yuanfang Guan27, Ming-Yi Hong13, Chao Huang28, Jinseub Hwang29, Joseph Ibrahim28, Paolo Inglese30, Anandhi Iyappan31, Qijia Jiang1, Yuriko Katsumata32, John S K Kauwe33, Arno Klein34, Dehan Kong28, Roland Krause25, Emilie Lalonde3, Mario Lauria10, Eunjee Lee28, Xihui Lin3, Zhandong Liu1, Julie Livingstone3, Benjamin A Logsdon5, Simon Lovestone35, Tsung-Wei Ma12, Ashutosh Malhotra31, Lara M Mangravite36, Taylor J Maxwell37, Emily Merrill38, John Nagorski1, Aishwarya Namasivayam25, Manjari Narayan1, Mufassra Naz31, Stephen J Newhouse39, Thea C Norman5, Ramil N Nurtdinov40, Yen-Jen Oyang11, Yudi Pawitan41, Shengwen Peng17, Mette A Peters42, Stephen R Piccolo8, Paurush Praveen43, Corrado Priami10, Veronica Y Sabelnykova3, Philipp Senger44, Xia Shen45, Andrew Simmons46, Aristeidis Sotiras16, Gustavo Stolovitzky47, Sabina Tangaro48, Andrea Tateo49, Yi-An Tung50, Nicholas J Tustison51, Erdem Varol16, George Vradenburg52, Michael W Weiner53, Guanghua Xiao12, Lei Xie54, Yang Xie12, Jia Xu12, Hojin Yang28, Xiaowei Zhan12, Yunyun Zhou12, Fan Zhu55, Hongtu Zhu28, Shanfeng Zhu56.
Abstract
Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.Entities:
Keywords: Azheimer's disease; Big data; Bioinformatics; Biomarkers; Cognitive decline; Crowdsource; Genetics; Imaging
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Year: 2016 PMID： 27079753 PMCID： PMC5474755 DOI： 10.1016/j.jalz.2016.02.006
Source DB: PubMed Journal: Alzheimers Dement ISSN： 1552-5260 Impact factor: 21.566