Xiaohui Yao
Xiaohui Yao
Verified email at pennmedicine.upenn.edu
TitleCited byYear
Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans
AJ Saykin, L Shen, X Yao, S Kim, K Nho, SL Risacher, VK Ramanan, ...
Alzheimer's & Dementia 11 (7), 792-814, 2015
1162015
Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules
X Yao, J Yan, K Liu, S Kim, K Nho, SL Risacher, CS Greene, JH Moore, ...
Bioinformatics 33 (20), 3250-3257, 2017
122017
Identification of associations between genotypes and longitudinal phenotypes via temporally-constrained group sparse canonical correlation analysis
X Hao, C Li, J Yan, X Yao, SL Risacher, AJ Saykin, L Shen, D Zhang, ...
Bioinformatics 33 (14), i341-i349, 2017
122017
Identifying multimodal intermediate phenotypes between genetic risk factors and disease status in Alzheimer¢s disease
X Hao, X Yao, J Yan, SL Risacher, AJ Saykin, D Zhang, L Shen, ...
Neuroinformatics 14 (4), 439-452, 2016
122016
A novel SCCA approach via truncated 1-norm and truncated group lasso for brain imaging genetics
L Du, K Liu, T Zhang, X Yao, J Yan, SL Risacher, J Han, L Guo, AJ Saykin, ...
Bioinformatics 34 (2), 278-285, 2017
102017
Two-dimensional enrichment analysis for mining high-level imaging genetic associations
X Yao, J Yan, S Kim, K Nho, SL Risacher, M Inlow, JH Moore, AJ Saykin, ...
Brain informatics 4 (1), 27, 2017
72017
Mapping longitudinal scientific progress, collaboration and impact of the Alzheimer¢s disease neuroimaging initiative
X Yao, J Yan, M Ginda, K Börner, AJ Saykin, L Shen, ...
PloS one 12 (11), e0186095, 2017
62017
Identifying associations between brain imaging phenotypes and genetic factors via a novel structured scca approach
L Du, T Zhang, K Liu, J Yan, X Yao, SL Risacher, AJ Saykin, J Han, L Guo, ...
International Conference on Information Processing in Medical Imaging, 543-555, 2017
62017
Longitudinal genotype-phenotype association study via temporal structure auto-learning predictive model
X Wang, J Yan, X Yao, S Kim, K Nho, SL Risacher, AJ Saykin, L Shen, ...
International Conference on Research in Computational Molecular Biology, 287-302, 2017
62017
Mining outcome-relevant brain imaging genetic associations via three-way sparse canonical correlation analysis in alzheimer¢s disease
X Hao, C Li, L Du, X Yao, J Yan, SL Risacher, AJ Saykin, L Shen, ...
Scientific reports 7, 44272, 2017
62017
Genome-wide network-based pathway analysis of CSF t-tau/Aâ1-42 ratio in the ADNI cohort
W Cong, X Meng, J Li, Q Zhang, F Chen, W Liu, Y Wang, S Cheng, X Yao, ...
BMC genomics 18 (1), 421, 2017
42017
Diagnosis-guided method for identifying multi-modality neuroimaging biomarkers associated with genetic risk factors in Alzheimer's disease
X Hao, J Yan, X Yao, SL Risacher, AJ Saykin, D Zhang, LI Shen
Biocomputing 2016: Proceedings of the Pacific Symposium, 108-119, 2016
42016
Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: a longitudinal study of the ADNI cohort
L Du, K Liu, L Zhu, X Yao, SL Risacher, L Guo, AJ Saykin, L Shen, ...
Bioinformatics 35 (14), i474-i483, 2019
32019
Fast Multi-Task SCCA Learning with Feature Selection for Multi-Modal Brain Imaging Genetics
L Du, K Liu, X Yao, SL Risacher, J Han, L Guo, AJ Saykin, L Shen
2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018
32018
Pattern discovery in brain imaging genetics via scca modeling with a generic non-convex penalty
L Du, K Liu, X Yao, J Yan, SL Risacher, J Han, L Guo, AJ Saykin, L Shen
Scientific reports 7 (1), 14052, 2017
32017
A fast scca algorithm for big data analysis in brain imaging genetics
Y Huang, L Du, K Liu, X Yao, SL Risacher, L Guo, AJ Saykin, L Shen, ...
Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging …, 2017
32017
Sparse Canonical Correlation Analysis via truncated ℓ1-norm with application to brain imaging genetics
L Du, T Zhang, K Liu, X Yao, J Yan, SL Risacher, L Guo, AJ Saykin, ...
2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2016
32016
Machine learning in brain imaging genomics
J Yan, L Du, X Yao, L Shen
Machine Learning and Medical Imaging, 411-434, 2016
32016
Targeted genetic analysis of cerebral blood flow imaging phenotypes implicates the INPP5D gene
X Yao, SL Risacher, K Nho, AJ Saykin, Z Wang, L Shen, ...
Neurobiology of aging 81, 213-221, 2019
22019
Predicting progressions of cognitive outcomes via high-order multi-modal multi-task feature learning
L Lu, H Wang, X Yao, S Risacher, A Saykin, L Shen
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018
22018
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Articles 1–20