Li Shen

发表

Fast Association Discovery in Derivative Transaction Collections

Li Shen, Hong Shen, Ling Cheng, 2000, Knowledge and Information Systems.

A Spatio-Temporal Modeling Method for Shape Representation

Fillia Makedon, Heng Huang, Li Shen, 2006, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06).

Sparse Bayesian multi-task learning for predicting cognitive outcomes from neuroimaging measures in Alzheimer's disease

Shannon L. Risacher, Andrew J. Saykin, Bhaskar D. Rao, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Motor Cortical Encoding of Hand Orientation in a 3-D Reach-to-grasp Task

Li Shen, 2007 .

Diagnosis Status Guided Brain Imaging Genetics Via Integrated Regression And Sparse Canonical Correlation Analysis

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Surface Harmonics for Shape Modeling

Heng Huang, Li Shen, 2007, 2007 IEEE International Conference on Image Processing.

Network-Guided Sparse Learning for Predicting Cognitive Outcomes from MRI Measures

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2013, MBIA.

Identification of Discriminative Imaging Proteomics Associations in Alzheimer's Disease via a Novel Sparse Correlation Model>

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2016, PSB.

Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, Bioinform..

Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via a Novel Structured SCCA Approach

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2017, IPMI.

Predicting Interrelated Alzheimer's Disease Outcomes via New Self-learned Structured Low-Rank Model

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, IPMI.

A Graph-Based Integration of Multimodal Brain Imaging Data for the Detection of Early Mild Cognitive Impairment (E-MCI)

Michael Weiner, Shannon L. Risacher, Andrew J. Saykin, 2013, MBIA.

Spherical parameterization for 3D surface analysis in volumetric images

Fillia Makedon, Li Shen, 2004, International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004..

New Probabilistic Multi-graph Decomposition Model to Identify Consistent Human Brain Network Modules

Yang Wang, Andrew J. Saykin, Heng Huang, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

Joint exploration and mining of memory-relevant brain anatomic and connectomic patterns via a three-way association model

Joaquín Goñi, Enrico Amico, Shannon L. Risacher, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

Pattern Visualization of Human Connectome Data

Yang Wang, Andrew J. Saykin, Hongyang Chao, 2012, EuroVis.

A spatio-temporal multi-modal data management and analysis environment for tracking MS lesions

Fillia Makedon, Andrew J. Saykin, Li Shen, 2003, 15th International Conference on Scientific and Statistical Database Management, 2003..

Fast surface alignment for cardiac spatio-temporal modeling: application to ischemic cardiac shape modeling

Fillia Makedon, Heng Huang, Li Shen, 2006, SPIE Medical Imaging.

Mining the Most Interesting Web Access Associations

Fillia Makedon, Li Shen, Ling Cheng, 2000, WebNet.

Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2011, 2011 International Conference on Computer Vision.

Deep Learning for Quality Control of Subcortical Brain 3D Shape Models

Lei Wang, Jessica A. Turner, Lars T. Westlye, 2018 .

Large-Scale Modeling of Parametric Surfaces Using Spherical Harmonics

Moo K. Chung, Li Shen, M. Chung, 2006, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06).

A Prediction Framework for Cardiac Resynchronization Therapy Via 4D Cardiac Motion Analysis

Fillia Makedon, Heng Huang, Li Shen, 2005, MICCAI.

The effect of reference panels and software tools on genotype imputation.

Li Shen, Sungeun Kim, Kwangsik Nho, 2011, AMIA ... Annual Symposium proceedings. AMIA Symposium.

An interactive 3D visualization and manipulation tool for effective assessment of angiogenesis and arteriogenesis using computed tomographic angiography

Fillia Makedon, Heng Huang, Ling Gao, 2005, SPIE Medical Imaging.

Identifying the Neuroanatomical Basis of Cognitive Impairment in Alzheimer's Disease by Correlation- and Nonlinearity-Aware Sparse Bayesian Learning

Andrew J. Saykin, Bhaskar D. Rao, Zhilin Zhang, 2014, IEEE Transactions on Medical Imaging.

Identifying Multimodal Intermediate Phenotypes Between Genetic Risk Factors and Disease Status in Alzheimer’s Disease

Daoqiang Zhang, Shannon L. Risacher, Andrew J. Saykin, 2016, Neuroinformatics.

Morphometric Analysis of Brain Structures for Improved Discrimination

Fillia Makedon, Andrew J. Saykin, Li Shen, 2003, MICCAI.

Statistical Inference on the Number of Cycles in Brain Networks

Moo K. Chung, Li Shen, Shih-Gu Huang, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimer's disease relevant SNPs

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, Bioinform..

Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer's Disease

Shannon L. Risacher, Andrew J. Saykin, Hua Wang, 2018, MICCAI.

Exploring Interestingness in a Computational Evolution System for the Genome-Wide Genetic Analysis of Alzheimer's Disease

Andrew J. Saykin, Jason H. Moore, Li Shen, 2013, GPTP.

Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort

Michael Weiner, Shannon L. Risacher, John D. West, 2010, NeuroImage.

Joint between-sample normalization and differential expression detection through ℓ0-regularized regression

Li Shen, Kefei Liu, Hui Jiang, 2019, BMC Bioinformatics.

Identification of associations between genotypes and longitudinal phenotypes via temporally-constrained group sparse canonical correlation analysis

Daoqiang Zhang, Shannon L. Risacher, Andrew J. Saykin, 2017, Bioinform..

Transcriptome-Guided Imaging Genetic Analysis via a Novel Sparse CCA Algorithm

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, GRAIL/MFCA/MICGen@MICCAI.

On design changes and site visa of architectural construction

Li Shen, 2010 .

Generating fuzzy semantic metadata describing spatial relations from images using the R-histogram

Fillia Makedon, Li Shen, Dina Q. Goldin, 2004, JCDL.

Weighted Fourier Series Representation and Its Application to Quantifying the Amount of Gray Matter

Moo K. Chung, Li Shen, Alan C. Evans, 2007, IEEE Transactions on Medical Imaging.

Shannon L. Risacher, John D. West, Andrew J. Saykin, 2010, NeuroImage.

Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction

Yuan Qi, Shannon L. Risacher, Andrew J. Saykin, 2010, MICCAI.

Interactive Machine Learning by Visualization: A Small Data Solution

Andrew J. Saykin, Huang Li, Shiaofen Fang, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Hemispherical Harmonic Surface Description and Applications to Medical Image Analysis

Fillia Makedon, Lei Zhang, Heng Huang, 2006, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06).

Human Connectome Module Pattern Detection Using a New Multi-graph MinMax Cut Model

Yang Wang, Andrew J. Saykin, Feiping Nie, 2014, MICCAI.

Brain explorer for connectomic analysis

Yang Wang, Joaquín Goñi, Shannon L. Risacher, 2017, Brain Informatics.

TROI - A training and research system for tracing regions of interest in brain images

Andrew J. Saykin, Li Shen, Ling Cheng, 2001, NeuroImage.

Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: a longitudinal study of the ADNI cohort

Lei Du, Li Shen, Lei Guo, 2019, Bioinform..

K-means+ method for improving gene selection for classification of microarray data

Fillia Makedon, Heng Huang, Li Shen, 2005, 2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05).

Data Brokers: Building Collections through Automated Negotiation

Fillia Makedon, Li Shen, Sheng Zhang, 2004, SETN.

A New Statistical Image Analysis Approach and Its Application to Hippocampal Morphometry

Shannon L. Risacher, John D. West, Andrew J. Saykin, 2016, MIAR.

Quantitative trait loci identification for brain endophenotypes via new additive model with random networks

Hong Chen, Shannon L. Risacher, Andrew J. Saykin, 2018, Bioinform..

Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, Bioinform..

Shape Analysis and Spatio-Temporal Tracking of Mesoscale Eddies in Miami Isopycnic Coordinate Ocean Model

Li Shen, Ramprasad Balasubramanian, Veena Moolani, 2006, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06).

A Novel Surface Registration Algorithm With Biomedical Modeling Applications

Fillia Makedon, Andrew J. Saykin, Heng Huang, 2007, IEEE Transactions on Information Technology in Biomedicine.

Multi-scale Voxel-Based Morphometry Via Weighted Spherical Harmonic Representation

Moo K. Chung, Li Shen, Richard J. Davidson, 2006, MIAR.

Morphometric Analysis of Hippocampal Shape in Mild Cognitive Impairment: An Imaging Genetics Study

Andrew J. Saykin, Moo K. Chung, Heng Huang, 2007, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering.

Prioritization of Cognitive Assessments in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data

Shannon L. Risacher, Andrew J. Saykin, Bo Peng, 2019, 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

GPU Accelerated Browser for Neuroimaging Genomics

Andrew J. Saykin, Huang Li, Jingwen Yan, 2018, Neuroinformatics.

MetaDL: A Digital Library of Metadata for Sensitive or Complex Research Data

Fillia Makedon, Andrew J. Saykin, Li Shen, 2002, ECDL.

New Algorithms for Efficient Mining of Association Rules

Li Shen, Hong Shen, Ling Cheng, 1999, Inf. Sci..

Regional reproducibility of pulsed arterial spin labeling perfusion imaging at 3T

Chen Lin, Yang Wang, Andrew J. Saykin, 2011, NeuroImage.

SCENS: a system for the mediated sharing of sensitive data

Fillia Makedon, Yan Zhao, Li Shen, 2003, 2003 Joint Conference on Digital Libraries, 2003. Proceedings..

Heritability Estimation of Reliable Connectomic Features

Joaquín Goñi, Enrico Amico, Andrew J. Saykin, 2018, CNI@MICCAI.

A novel SCCA approach via truncated ℓ1-norm and truncated group lasso for brain imaging genetics

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2017, Bioinform..

Identifying Connectome Module Patterns via New Balanced Multi-graph Normalized Cut

Yang Wang, Lin Yan, Joaquín Goñi, 2015, MICCAI.

EVALUATION METRICS FOR USER-CENTERED RANKING OF CONTENT IN METADLs

Fillia Makedon, Andrew J. Saykin, Li Shen, 2004 .

Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2014, Bioinform..

A New Sparse Simplex Model for Brain Anatomical and Genetic Network Analysis

Andrew J. Saykin, Feiping Nie, Jingwen Yan, 2013, MICCAI.

Network-based analysis of genetic variants associated with hippocampal volume in Alzheimer’s disease: a study of ADNI cohorts

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2016, BioData Mining.

Predicting progressions of cognitive outcomes via high-order multi-modal multi-task feature learning

Shannon L. Risacher, Andrew J. Saykin, Hua Wang, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

BECA: A Software Tool for Integrated Visualization of Human Brain Data

Joaquín Goñi, Andrew J. Saykin, Huang Li, 2017, BI.

Spherical mapping for processing of 3D closed surfaces

Fillia Makedon, Li Shen, F. Makedon, 2006, Image Vis. Comput..

Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2016, Bioinform..

A Framework for 3D Analysis of Facial Morphology in Fetal Alcohol Syndrome

Shiaofen Fang, Li Shen, Jing Wan, 2010, MIAR.

Mining Flexible Multiple-Level Association Rules in All Concept Hierarchies (Extended Abstract)

Li Shen, Hong Shen, 1998, DEXA.

Structural Brain Network Constrained Neuroimaging Marker Identification for Predicting Cognitive Functions

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2013, IPMI.

Multigraph Visualization for Feature Classification of Brain Network Data

Joaquín Goñi, Andrew J. Saykin, Huang Li, 2016, EuroVA@EuroVis.

A Novel Structure-Aware Sparse Learning Algorithm for Brain Imaging Genetics

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2014, MICCAI.

Functional analysis of cardiac MR images using SPHARM modeling

Fillia Makedon, Heng Huang, Ling Gao, 2005, SPIE Medical Imaging.

A Fast SCCA Algorithm for Big Data Analysis in Brain Imaging Genetics

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2017, GRAIL/MFCA/MICGen@MICCAI.

Computational genetics analysis of grey matter density in Alzheimer’s disease

Andrew J. Saykin, Ting Hu, Jason H. Moore, 2014, BioData Mining.

Efficient Registration of 3D SPHARM Surfaces

Fillia Makedon, Andrew J. Saykin, Heng Huang, 2007, Fourth Canadian Conference on Computer and Robot Vision (CRV '07).

Fourier method for large-scale surface modeling and registration

Andrew J. Saykin, Li Shen, Sungeun Kim, 2009, Comput. Graph..

Hippocampal shape analysis: surface-based representation and classification

Fillia Makedon, Andrew J. Saykin, Li Shen, 2003, SPIE Medical Imaging.

Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2011, MICCAI.

Identifying significant gene‐environment interactions using a combination of screening testing and hierarchical false discovery rate control

Andrew J. Saykin, Jason H. Moore, Li Shen, 2016, Genetic epidemiology.

The role of visualization and 3-D printing in biological data mining

Andrew J. Saykin, Jason H. Moore, Li Shen, 2015, BioData Mining.

Identifying Neuroimaging and Proteomic Biomarkers for MCI and AD via the Elastic Net

Yuan Qi, Michael Weiner, Shannon L. Risacher, 2011, MBIA.

GN-SCCA: GraphNet Based Sparse Canonical Correlation Analysis for Brain Imaging Genetics

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2015, BIH.

Spatio-temporal analysis tool for modeling pulmonary nodules in MR images

Fillia Makedon, Heng Huang, Ling Gao, 2006, SPIE Medical Imaging.

Two-Dimensional Enrichment Analysis for Mining High-Level Imaging Genetic Associations

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2015, BIH.

A Unified Model for Robust Differential Expression Analysis of RNA-Seq Data

Li Shen, Kefei Liu, Hui Jian, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, NIPS.

Multimodal Neuroimaging Predictors for Cognitive Performance Using Structured Sparse Learning

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2012, MBIA.

Voxelwise gene-wide association study (vGeneWAS): Multivariate gene-based association testing in 731 elderly subjects

Michael Weiner, Andrew J. Saykin, Paul M. Thompson, 2011, NeuroImage.

Hierarchical Structured Sparse Learning for Schizophrenia Identification

Daoqiang Zhang, Li Shen, Mingliang Wang, 2019, Neuroinformatics.

Data synthesis and tool development for exploring imaging genomic patterns

John D. West, Andrew J. Saykin, Li Shen, 2009, 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, Briefings Bioinform..

Mining Regional Imaging Genetic Associations via Voxel-wise Enrichment Analysis

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2019, 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

Accelerating Sparse Canonical Correlation Analysis for Large Brain Imaging Genetics Data

Andrew J. Saykin, Lei Du, Jingwen Yan, 2014, XSEDE '14.

Identifying Imaging Markers for Predicting Cognitive Assessments Using Wasserstein Distances Based Matrix Regression

Li Shen, Cheng Deng, Xiaohui Yao, 2019, Front. Neurosci..

Hippocampal Surface Mapping of Genetic Risk Factors in AD via Sparse Learning Models

Michael Weiner, Shannon L. Risacher, Andrew J. Saykin, 2011, MICCAI.

Joint identification of imaging and proteomics biomarkers of Alzheimer's disease using network-guided sparse learning

Andrew J. Saykin, Jingwen Yan, Jason H. Moore, 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

Multiple incomplete views clustering via non-negative matrix factorization with its application in Alzheimer's disease analysis

Shannon L. Risacher, Andrew J. Saykin, Kai Liu, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

PARP1 Gene Variation and Microglial Activity on [11C]PBR28 PET in Older Adults at Risk for Alzheimer's Disease

Shannon L. Risacher, John D. West, Andrew J. Saykin, 2013, MBIA.

Integrated Visualization of Human Brain Connectome Data

Yang Wang, Joaquín Goñi, Shannon L. Risacher, 2015, BIH.

Mining 3D Shape Data for Morphometric Pattern Discovery

Fillia Makedon, Li Shen, 2009, Encyclopedia of Data Warehousing and Mining.

Network-based genome wide study of hippocampal imaging phenotype in Alzheimer's Disease to identify functional interaction modules

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging

Jessica A. Turner, Lars T. Westlye, Li Shen, 2017 .

Interactive object extraction by merging regions with k-global maximal similarity

Jiang Wu, Jingwen Yan, Li Shen, 2013, Neurocomputing.

Diagnosis-Guided Method for Identifying Multi-Modality Neuroimaging Biomarkers Associated with Genetic Risk Factors in Alzheimer's Disease

Daoqiang Zhang, Shannon L. Risacher, Andrew J. Saykin, 2016, PSB.

Structured sparse CCA for brain imaging genetics via graph OSCAR

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2016, BMC Systems Biology.

Tissue‐specific network‐based genome wide study of amygdala imaging phenotypes to identify functional interaction modules

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, Bioinform..

The three NITRCs: Software, data and cloud computing for brain science and dementia research

Li Shen, David Kennedy, Nina Preuss, 2013, Alzheimer's & Dementia.

Fast Multi-Task SCCA Learning with Feature Selection for Multi-Modal Brain Imaging Genetics

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

A surface-based approach for classification of 3D neuroanatomic structures

Fillia Makedon, Andrew J. Saykin, Li Shen, 2004, Intell. Data Anal..

An analysis on building craft in Yin Zao Fa Yuan: To “Ti Zhan” as example

Li Shen, 2011, 2011 International Conference on Multimedia Technology.

A clustering-based approach for prediction of cardiac resynchronization therapy

Fillia Makedon, Heng Huang, Ling Gao, 2005, SAC '05.

Longitudinal Genotype-Phenotype Association Study via Temporal Structure Auto-learning Predictive Model

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, RECOMB.

Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics

M. Jorge Cardoso, Mert R. Sabuncu, Li Shen, 2017, Lecture Notes in Computer Science.

A system framework for the integration and analysis of multi-modal spatiotemporal data streams: a case study in MS lesion analysis

Fillia Makedon, Andrew J. Saykin, Li Shen, 2003, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings..

Two-dimensional enrichment analysis for mining high-level imaging genetic associations

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2016, Brain Informatics.

Identifying Candidate Genetic Associations with MRI-Derived AD-Related ROI via Tree-Guided Sparse Learning

Daoqiang Zhang, Li Shen, Xiaohui Yao, 2019, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Erratum to: Improving protein order-disorder classification using charge-hydropathy plots

Li Shen, Fei Huang, Bin Xue, 2015, BMC Bioinformatics.

Principles of Computational Modeling in NeuroscienceDavid Sterratt, Bruce Graham, Andrew Gillies and David Willshaw

Li Shen, 2012, Briefings Bioinform..

Genetic Clustering on the Hippocampal Surface for Genome-Wide Association Studies

Andrew J. Saykin, Paul M. Thompson, Li Shen, 2013, MICCAI.

Shape-based discriminative analysis of combined bilateral hippocampi using multiple object alignment

Fillia Makedon, Andrew J. Saykin, Li Shen, 2004, SPIE Medical Imaging.

Data synthesis and method evaluation for brain imaging genetics

Andrew J. Saykin, Jingwen Yan, Jason H. Moore, 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

基于 AMESim 的一种双作用往复抽油泵仿真研究

Li Shen, Yu Jun, 于俊, 2017 .

Surface Alignment of 3D Spherical Harmonic Models: Application to Cardiac MRI Analysis

Fillia Makedon, Heng Huang, Li Shen, 2005, MICCAI.

Genome-wide analysis reveals novel genes influencing temporal lobe structure with relevance to neurodegeneration in Alzheimer's disease

Michael Weiner, Andrew J. Saykin, Paul M. Thompson, 2010, NeuroImage.

GENETIC FINDINGS USING ADNI MULTIMODAL QUANTITATIVE PHENOTYPES: A 2016 UPDATE

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, Alzheimer's & Dementia.

Relationship of microglial activation measured by [11C]PBR28 PET, atrophy on MRI and plasma biomarkers in individuals with and at risk for Alzheimer's disease

Yang Wang, Li Shen, Shannon Risacher, 2013, Alzheimer's & Dementia.

Metabolic network failures in Alzheimer's disease: A biochemical road map

Michael W. Weiner, Shannon L. Risacher, Andrew J. Saykin, 2017, Alzheimer's & Dementia.

Genetic architecture of subcortical brain structures in 38,851 individuals

Benjamin S Aribisala, Tien Yin Wong, Wiro J Niessen, 2019, Nature Genetics.

The Interleukin 3 Gene (IL3) Contributes to Human Brain Volume Variation by Regulating Proliferation and Survival of Neural Progenitors

Andrew J. Saykin, Li Shen, Guillén Fernández, 2012, PloS one.

Genetic Interactions Explain Variance in Cingulate Amyloid Burden: An AV-45 PET Genome-Wide Association and Interaction Study in the ADNI Cohort

Andrew J. Saykin, Jingwen Yan, Li Shen, 2015, BioMed research international.

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

Norbert Schuff, Michael W. Weiner, Robert C. Green, 2016, Nature Communications.

Voxel and surface-based topography of memory and executive deficits in mild cognitive impairment and Alzheimer’s disease

Shannon L. Risacher, Andrew J. Saykin, Li Shen, 2012, Brain Imaging and Behavior.

The genetic architecture of the human cerebral cortex

Anders M. Dale, Robert C. Green, Shannon L. Risacher, 2020, Science.

Cortical surface biomarkers for predicting cognitive outcomes using group l 2,1 norm

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2015, Neurobiology of Aging.

Robust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns

Norbert Schuff, Robert C. Green, Andrew J. Saykin, 2017 .

Association of common genetic variants in GPCPD1 with scaling of visual cortical surface area in humans

Norbert Schuff, Adrian Preda, John Kornak, 2012, Proceedings of the National Academy of Sciences.

Author Correction: Multimodal hippocampal subfield grading for Alzheimer’s disease classification

Norbert Schuff, Michael W. Weiner, Robert C. Green, 2020, Scientific Reports.

Mapre2 as a novel Alzheimer's disease target gene from gwas of CSF amyloid beta 1-42, tau and hyperphosphorylated tau in the ADNI cohort

Michael W. Weiner, Shannon L. Risacher, Andrew J. Saykin, 2015, Alzheimer's & Dementia.

Novel genetic loci associated with hippocampal volume

Benjamin S Aribisala, Wiro J Niessen, Peter Kochunov, 2017, Nature Communications.

Volumetric, cortical thickness and grey matter density changes on MRI over 12 months: Relationship to conversion status in the ADNI cohort

Shannon L. Risacher, Andrew J. Saykin, Li Shen, 2009, Alzheimer's & Dementia.

A commonly carried allele of the obesity-related FTO gene is associated with reduced brain volume in the healthy elderly

Michael W. Weiner, Andrew J. Saykin, Paul M. Thompson, 2010, Proceedings of the National Academy of Sciences.

Pattern Discovery in Brain Imaging Genetics via SCCA Modeling with a Generic Non-convex Penalty

Lei Du, Jingwen Yan, Li Shen, 2017, Scientific Reports.

APOE effect on Alzheimer’s biomarkers in older adults with significant memory concern

Michael W. Weiner, Shannon L. Risacher, Andrew J. Saykin, 2015 .

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Benjamin S Aribisala, Wiro J Niessen, Peter Kochunov, 2016, Nature Neuroscience.

Genome-wide analysis reveals novel genes in fl uencing temporal lobe structure with relevance to neurodegeneration in Alzheimer ' s disease

Michael W. Weiner, Andrew J. Saykin, Paul M. Thompson, 2010 .

Genetic findings using ADNI multimodal quantitative phenotypes: A 2014 update

Michael W. Weiner, Robert C. Green, Shannon L. Risacher, 2015, Alzheimer's & Dementia.

Genome-wide pathway analysis of memory impairment in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks

Michael W. Weiner, Shannon L. Risacher, Andrew J. Saykin, 2012, Brain Imaging and Behavior.

Visual exploration of genetic association with voxel-based imaging phenotypes in an MCI/AD study

Andrew J. Saykin, Li Shen, Sungeun Kim, 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Genetic studies of plasma analytes identify novel potential biomarkers for several complex traits

Norbert Schuff, Michael W. Weiner, Robert C. Green, 2016, Scientific Reports.

Amyloid pathway-based candidate gene analysis of [11C]PiB-PET in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort

Michael W. Weiner, Shannon L. Risacher, Andrew J. Saykin, 2011, Brain Imaging and Behavior.

Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium

Anders M. Dale, Robert C. Green, Shannon L. Risacher, 2018, bioRxiv.

Relationship of microglial activation measured by [11C]PBR28 PET, atrophy on MRI and plasma biomarkers in individuals with and at-risk for Alzheimer's disease

Yang Wang, Li Shen, Shannon Risacher, 2013, Alzheimer's & Dementia.

Protective variant for hippocampal atrophy identified by whole exome sequencing

Li Shen, Magda Tsolaki, Clifford R Jack, 2015, Annals of neurology.

Large-scale genomics unveil polygenic architecture of human cortical surface area

Norbert Schuff, Anders M. Dale, Robert C. Green, 2015, Nature Communications.

P2-077: Comparison of manual and automated determination of hippocampal volumes in MCI and older adults with cognitive complaints

Andrew J. Saykin, Li Shen, Laura A. Flashman, 2008, Alzheimer's & Dementia.

Development of refractive error in individual children with regressed retinopathy of prematurity.

Li Shen, Jingyun Wang, Li Shen, 2013, Investigative ophthalmology & visual science.

Association analysis of rare variants near the APOE region with CSF and neuroimaging biomarkers of Alzheimer’s disease

Michael W. Weiner, Robert C. Green, Shannon L. Risacher, 2017, BMC Medical Genomics.

GWAS of longitudinal amyloid accumulation on 18F-florbetapir PET in Alzheimer's disease implicates microglial activation gene IL1RAP.

Li Shen, Clifford R Jack, Arthur W Toga, 2015, Brain : a journal of neurology.

Machine learning in brain imaging genomics

Lei Du, Li Shen, Li Shen, 2016 .

Hippocampus as a Predictor of Cognitive Performance : Comparative Evaluation of Analytical Methods and Morphometric Measures

Shannon L. Risacher, Andrew J. Saykin, Zhilin Zhang, 2012 .

FOURIER METHODS FOR 3D SURFACE MODELING AND ANALYSIS

Andrew J. Saykin, Li Shen, John D. West, 2011 .

Hippocampal transcriptome-guided genetic analysis of correlated episodic memory phenotypes in Alzheimer's disease

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2015, Front. Genet..

AbstractPoster presentation: Imaging posterIC-P1-054: Comparison of manual and automated determination of hippocampal volumes in MCI and older adults with cognitive complaints

Andrew J. Saykin, Li Shen, Laura A. Flashman, 2008 .

Genetic Architecture of Subcortical Brain Structures in Over 40,000 Individuals Worldwide

Michael W. Weiner, Anders M. Dale, Robert C. Green, 2017, bioRxiv.

Genetic pathway‐based hierarchical clustering analysis of older adults with cognitive complaints and amnestic mild cognitive impairment using clinical and neuroimaging phenotypes

Li Shen, Jason H. Moore, Li Shen, 2010, American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics.

APOE and BCHE as modulators of cerebral amyloid deposition: a florbetapir PET genome-wide association study

Michael W. Weiner, Robert C. Green, Shannon L. Risacher, 2013, Molecular Psychiatry.

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Michael W. Weiner, Robert C. Green, Andrew J. Saykin, 2015, Alzheimer's & Dementia.