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  • Li Shen
2020

A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease

Liu, M., Li, F., Yan, H., Wang, K., Ma, Y., Shen, L. & Xu, M., Mar 2020, In : NeuroImage. 208, 116459.

Research output: Contribution to journalArticle

Open Access
5 Scopus citations

A super-combo-drug test to detect adverse drug events and drug interactions from electronic health records in the era of polypharmacy

Zhu, A., Zeng, D., Shen, L., Ning, X., Li, L. & Zhang, P., May 15 2020, In : Statistics in Medicine. 39, 10, p. 1458-1472 15 p.

Research output: Contribution to journalArticle

Brain Imaging Genomics: Integrated Analysis and Machine Learning

Shen, L. & Thompson, P. M., Jan 2020, In : Proceedings of the IEEE. 108, 1, p. 125-162 38 p., 8886705.

Research output: Contribution to journalArticle

Brain-wide structural connectivity alterations under the control of Alzheimer risk genes

Yan, J., Vinesh Raja, V., Huang, Z., Amico, E., Nho, K., Fang, S., Sporns, O., Wu, Y. C., Saykin, A., Goñi, J. & Shen, L., 2020, In : International Journal of Computational Biology and Drug Design. 13, 1, p. 58-70 13 p.

Research output: Contribution to journalArticle

Deep Network-Based Feature Selection for Imaging Genetics: Application to Identifying Biomarkers for Parkinson's Disease

Kim, M., Won, J. H., Hong, J., Kwon, J., Park, H. & Shen, L., Apr 2020, ISBI 2020 - 2020 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, p. 1920-1923 4 p. 9098471. (Proceedings - International Symposium on Biomedical Imaging; vol. 2020-April).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured SCCA approach

Du, L., Liu, K., Yao, X., Risacher, S. L., Han, J., Saykin, A. J., Guo, L. & Shen, L., Apr 2020, In : Medical Image Analysis. 61, 101656.

Research output: Contribution to journalArticle

1 Scopus citations

Drug-drug interaction prediction based on co-medication patterns and graph matching

Chiang, W. H., Shen, L., Li, L. & Ning, X., 2020, In : International Journal of Computational Biology and Drug Design. 13, 1, p. 36-57 22 p.

Research output: Contribution to journalArticle

FAM222A encodes a protein which accumulates in plaques in Alzheimer’s disease

The Alzheimer Disease Neuroimaging Initiative, Dec 1 2020, In : Nature communications. 11, 1, 411.

Research output: Contribution to journalArticle

Open Access
2 Scopus citations

Functional brain architecture is associated with the rate of tau accumulation in Alzheimer’s disease

Alzheimer’s Disease Neuroimaging Initiative (ADNI), Dec 1 2020, In : Nature communications. 11, 1, 347.

Research output: Contribution to journalArticle

Open Access
5 Scopus citations

Hierarchical Structured Sparse Learning for Schizophrenia Identification

Wang, M., Hao, X., Huang, J., Wang, K., Shen, L., Xu, X., Zhang, D. & Liu, M., Jan 1 2020, In : Neuroinformatics. 18, 1, p. 43-57 15 p.

Research output: Contribution to journalArticle

Ideas for how informaticians can get involved with COVID-19 research

Moore, J. H., Barnett, I., Boland, M. R., Chen, Y., Demiris, G., Gonzalez-Hernandez, G., Herman, D. S., Himes, B. E., Hubbard, R. A., Kim, D., Morris, J. S., Mowery, D. L., Ritchie, M. D., Shen, L., Urbanowicz, R. & Holmes, J. H., May 12 2020, In : BioData Mining. 13, 1, 3.

Research output: Contribution to journalReview article

Open Access

Identifying diagnosis-specific genotype-phenotype associations via joint multitask sparse canonical correlation analysis and classification

Alzheimer’s Disease Neuroimaging Initiative, Jul 1 2020, In : Bioinformatics (Oxford, England). 36, 1, p. i371-i379

Research output: Contribution to journalArticle

Open Access

Joint Multi-Modal Longitudinal Regression and Classification for Alzheimer's Disease Prediction

Brand, L., Nichols, K., Wang, H., Shen, L. & Huang, H., Jun 2020, In : IEEE Transactions on Medical Imaging. 39, 6, p. 1845-1855 11 p., 8932589.

Research output: Contribution to journalArticle

Mining and visualizing high-order directional drug interaction effects using the FAERS database

Yao, X., Tsang, T., Sun, Q., Quinney, S., Zhang, P., Ning, X., Li, L. & Shen, L., Mar 18 2020, In : BMC medical informatics and decision making. 20, 50.

Research output: Contribution to journalArticle

Open Access

Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease

for the Alzheimer's Disease Neuroimaging Initiative, Feb 2020, In : Medical Image Analysis. 60, 101625.

Research output: Contribution to journalArticle

6 Scopus citations

Predicting Longitudinal Outcomes of Alzheimer's Disease via a Tensor-Based Joint Classification and Regression Model

Alzheimer’s Disease Neuroimaging Initiative, Jan 1 2020, In : Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 25, p. 7-18 12 p.

Research output: Contribution to journalArticle

1 Scopus citations

Regional imaging genetic enrichment analysis

Yao, X., Cong, S., Yan, J., Risacher, S. L., Saykin, A. J., Moore, J. H. & Shen, L., Apr 15 2020, In : Bioinformatics. 36, 8, p. 2554-2560 7 p.

Research output: Contribution to journalArticle

1 Scopus citations

The genetic architecture of the human cerebral cortex

Enhancing NeuroImaging Genetics through Meta-Analysis Consortium (ENIGMA)-Genetics working group, Mar 20 2020, In : Science. 367, 6484, aay6690.

Research output: Contribution to journalArticle

34 Scopus citations

Volumetric GWAS of medial temporal lobe structures identifies an ERC1 locus using ADNI high-resolution T2-weighted MRI data

UK Brain Expression Consortium & Alzheimer's Disease Neuroimaging Initiative, Nov 2020, In : Neurobiology of Aging. 95, p. 81-93 13 p.

Research output: Contribution to journalArticle

Open Access
2019

A dirty multi-task learning method for multi-modal brain imaging genetics

for the Alzheimer’s Disease Neuroimaging Initiative, Jan 1 2019, Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings. Shen, D., Yap, P-T., Liu, T., Peters, T. M., Khan, A., Staib, L. H., Essert, C. & Zhou, S. (eds.). Springer, p. 447-455 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11767 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

A Novel Joint Brain Network Analysis Using Longitudinal Alzheimer’s Disease Data

The Alzheimer’s Disease Neuroimaging Initiative, Dec 1 2019, In : Scientific reports. 9, 1, 19589.

Research output: Contribution to journalArticle

Open Access
1 Scopus citations

A unified model for joint normalization and differential gene expression detection in RNA-seq data

Liu, K., Ye, J., Yang, Y., Shen, L. & Jiang, H., Mar 1 2019, In : IEEE/ACM Transactions on Computational Biology and Bioinformatics. 16, 2, p. 442-454 13 p., 8249873.

Research output: Contribution to journalArticle

4 Scopus citations

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

Liu, K., Shen, L. & Jian, H., Jan 21 2019, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. Schmidt, H., Griol, D., Wang, H., Baumbach, J., Zheng, H., Callejas, Z., Hu, X., Dickerson, J. & Zhang, L. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 437-442 6 p. 8621331. (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Diagnosis status guided brain imaging genetics via integrated regression and sparse canonical correlation analysis

Du, L., Liu, K., Yao, X., Risacher, S. L., Guo, L., Saykin, A. J. & Shen, L., Apr 2019, ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, p. 356-359 4 p. 8759489. (Proceedings - International Symposium on Biomedical Imaging; vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Diffeomorphic Metric Learning and Template Optimization for Registration-Based Predictive Models

Mussabayeva, A., Pisov, M., Kurmukov, A., Kroshnin, A., Denisova, Y., Shen, L., Cong, S., Wang, L. & Gutman, B., Jan 1 2019, Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy - 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Proceedings. Zhu, D., Yan, J., Huang, H., Shen, L., Thompson, P. M., Westin, C-F., Pennec, X., Joshi, S., Nielsen, M., Sommer, S., Fletcher, T. & Durrleman, S. (eds.). Springer, p. 151-161 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11846 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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

Du, L., Liu, K., Yao, X., Risacher, S. L., Han, J., Guo, L., Saykin, A. J. & Shen, L., Jan 21 2019, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. Schmidt, H., Griol, D., Wang, H., Baumbach, J., Zheng, H., Callejas, Z., Hu, X., Dickerson, J. & Zhang, L. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 356-361 6 p. 8621298. (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Genetic architecture of subcortical brain structures in 38,851 individuals

Satizabal, C. L., Adams, H. H. H., Hibar, D. P., White, C. C., Knol, M. J., Stein, J. L., Scholz, M., Sargurupremraj, M., Jahanshad, N., Roshchupkin, G. V., Smith, A. V., Bis, J. C., Jian, X., Luciano, M., Hofer, E., Teumer, A., van der Lee, S. J., Yang, J., Yanek, L. R., Lee, T. V. & 269 others, Li, S., Hu, Y., Koh, J. Y., Eicher, J. D., Desrivières, S., Arias-Vasquez, A., Chauhan, G., Athanasiu, L., Rentería, M. E., Kim, S., Hoehn, D., Armstrong, N. J., Chen, Q., Holmes, A. J., den Braber, A., Kloszewska, I., Andersson, M., Espeseth, T., Grimm, O., Abramovic, L., Alhusaini, S., Milaneschi, Y., Papmeyer, M., Axelsson, T., Ehrlich, S., Roiz-Santiañez, R., Kraemer, B., Håberg, A. K., Jones, H. J., Pike, G. B., Stein, D. J., Stevens, A., Bralten, J., Vernooij, M. W., Harris, T. B., Filippi, I., Witte, A. V., Guadalupe, T., Wittfeld, K., Mosley, T. H., Becker, J. T., Doan, N. T., Hagenaars, S. P., Saba, Y., Cuellar-Partida, G., Amin, N., Hilal, S., Nho, K., Mirza-Schreiber, N., Arfanakis, K., Becker, D. M., Ames, D., Goldman, A. L., Lee, P. H., Boomsma, D. I., Lovestone, S., Giddaluru, S., Le Hellard, S., Mattheisen, M., Bohlken, M. M., Kasperaviciute, D., Schmaal, L., Lawrie, S. M., Agartz, I., Walton, E., Tordesillas-Gutierrez, D., Davies, G. E., Shin, J., Ipser, J. C., Vinke, L. N., Hoogman, M., Jia, T., Burkhardt, R., Klein, M., Crivello, F., Janowitz, D., Carmichael, O., Haukvik, U. K., Aribisala, B. S., Schmidt, H., Strike, L. T., Cheng, C. Y., Risacher, S. L., Pütz, B., Fleischman, D. A., Assareh, A. A., Mattay, V. S., Buckner, R. L., Mecocci, P., Dale, A. M., Cichon, S., Boks, M. P., Matarin, M., Penninx, B. W. J. H., Calhoun, V. D., Chakravarty, M. M., Marquand, A. F., Macare, C., Kharabian Masouleh, S., Oosterlaan, J., Amouyel, P., Hegenscheid, K., Rotter, J. I., Schork, A. J., Liewald, D. C. M., de Zubicaray, G. I., Wong, T. Y., Shen, L., Sämann, P. G., Brodaty, H., Roffman, J. L., de Geus, E. J. C., Tsolaki, M., Erk, S., van Eijk, K. R., Cavalleri, G. L., van der Wee, N. J. A., McIntosh, A. M., Gollub, R. L., Bulayeva, K. B., Bernard, M., Richards, J. S., Himali, J. J., Loeffler, M., Rommelse, N., Hoffmann, W., Westlye, L. T., Valdés Hernández, M. C., Hansell, N. K., van Erp, T. G. M., Wolf, C., Kwok, J. B. J., Vellas, B., Heinz, A., Olde Loohuis, L. M., Delanty, N., Ho, B. C., Ching, C. R. K., Shumskaya, E., Singh, B., Hofman, A., van der Meer, D., Homuth, G., Psaty, B. M., Bastin, M. E., Montgomery, G. W., Foroud, T. M., Reppermund, S., Hottenga, J. J., Simmons, A., Meyer-Lindenberg, A., Cahn, W., Whelan, C. D., van Donkelaar, M. M. J., Yang, Q., Hosten, N., Green, R. C., Thalamuthu, A., Mohnke, S., Hulshoff Pol, H. E., Lin, H., Jack, C. R., Schofield, P. R., Mühleisen, T. W., Maillard, P., Potkin, S. G., Wen, W., Fletcher, E., Toga, A. W., Gruber, O., Huentelman, M., Davey Smith, G., Launer, L. J., Nyberg, L., Jönsson, E. G., Crespo-Facorro, B., Koen, N., Greve, D. N., Uitterlinden, A. G., Weinberger, D. R., Steen, V. M., Fedko, I. O., Groenewold, N. A., Niessen, W. J., Toro, R., Tzourio, C., Longstreth, W. T., Ikram, M. K., Smoller, J. W., van Tol, M. J., Sussmann, J. E., Paus, T., Lemaître, H., Schroeter, M. L., Mazoyer, B., Andreassen, O. A., Holsboer, F., Depondt, C., Veltman, D. J., Turner, J. A., Pausova, Z., Schumann, G., van Rooij, D., Djurovic, S., Deary, I. J., McMahon, K. L., Müller-Myhsok, B., Brouwer, R. M., Soininen, H., Pandolfo, M., Wassink, T. H., Cheung, J. W., Wolfers, T., Martinot, J. L., Zwiers, M. P., Nauck, M., Melle, I., Martin, N. G., Kanai, R., Westman, E., Kahn, R. S., Sisodiya, S. M., White, T., Saremi, A., van Bokhoven, H., Brunner, H. G., Völzke, H., Wright, M. J., van ‘t Ent, D., Nöthen, M. M., Ophoff, R. A., Buitelaar, J. K., Fernández, G., Sachdev, P. S., Rietschel, M., van Haren, N. E. M., Fisher, S. E., Beiser, A. S., Francks, C., Saykin, A., Mather, K. A., Romanczuk-Seiferth, N., Hartman, C. A., DeStefano, A. L., Heslenfeld, D. J., Weiner, M. W., Walter, H., Hoekstra, P. J., Nyquist, P. A., Franke, B., Bennett, D. A., Grabe, H. J., Johnson, A. D., Chen, C., van Duijn, C. M., Lopez, O. L., Fornage, M., Wardlaw, J. M., Schmidt, R., DeCarli, C., De Jager, P. L., Villringer, A., Debette, S., Gudnason, V., Medland, S. E., Shulman, J. M., Thompson, P. M., Seshadri, S. & Ikram, M. A., Nov 1 2019, In : Nature genetics. 51, 11, p. 1624-1636 13 p.

Research output: Contribution to journalArticle

20 Scopus citations

Genome-wide network-assisted association and enrichment study of amyloid imaging phenotype in alzheimer’s disease

Alzheimer’s Disease Neuroimaging Initiative, Jan 1 2019, In : Current Alzheimer research. 16, 13, p. 1163-1174 12 p.

Research output: Contribution to journalArticle

2 Scopus citations

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

Hao, X., Yao, X., Risacher, S. L., Saykin, A. J., Yu, J., Wang, H., Tan, L., Shen, L. & Zhang, D., Nov 1 2019, In : IEEE/ACM Transactions on Computational Biology and Bioinformatics. 16, 6, p. 1986-1996 11 p., 8355682.

Research output: Contribution to journalArticle

Identifying imaging markers for predicting cognitive assessments using wasserstein distances based matrix regression

Yan, J., Deng, C., Luo, L., Wang, X., Yao, X., Shen, L. & Huang, H., 2019, In : Frontiers in Neuroscience. 13, JUL, 668.

Research output: Contribution to journalArticle

Open Access

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

Du, L., Liu, K., Zhu, L., Yao, X., Risacher, S. L., Guo, L., Saykin, A. J. & Shen, L., Jul 15 2019, In : Bioinformatics. 35, 14, p. i474-i483 btz320.

Research output: Contribution to journalArticle

Open Access
6 Scopus citations

Improved prediction of cognitive outcomes via globally aligned imaging biomarker enrichments over progressions

for the ADNI, 2019, Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings. Shen, D., Yap, P-T., Liu, T., Peters, T. M., Khan, A., Staib, L. H., Essert, C. & Zhou, S. (eds.). Springer, p. 140-148 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11767 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Interactive Machine Learning by Visualization: A Small Data Solution

Li, H., Fang, S., Mukhopadhyay, S., Saykin, A. J. & Shen, L., Jan 22 2019, Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018. Song, Y., Liu, B., Lee, K., Abe, N., Pu, C., Qiao, M., Ahmed, N., Kossmann, D., Saltz, J., Tang, J., He, J., Liu, H. & Hu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 3513-3521 9 p. 8621952. (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Joint between-sample normalization and differential expression detection through 0-regularized regression

Liu, K., Shen, L. & Jiang, H., Dec 2 2019, In : BMC bioinformatics. 20, 593.

Research output: Contribution to journalArticle

Open Access

Mining Directional Drug Interaction Effects on Myopathy Using the FAERS Database

Chasioti, D., Yao, X., Zhang, P., Lerner, S., Quinney, S. K., Ning, X., Li, L. & Shen, L., Sep 2019, In : IEEE Journal of Biomedical and Health Informatics. 23, 5, p. 2156-2163 8 p., 8485332.

Research output: Contribution to journalArticle

2 Scopus citations

Mining regional imaging genetic associations via voxel-wise enrichment analysis

Yao, X., Cong, S., Yan, J., Risacher, S. L., Saykin, A. J., Moore, J. H. & Shen, L., May 2019, 2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 8834450. (2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Multimodal Brain Image Analysis (MBIA)

Zhu, D., Yan, J., Huang, H., Shen, L., Thompson, P. M. & Westin, C. F., Jan 1 2019, In : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11846 LNCS

Research output: Contribution to journalEditorial

Multimodal Hippocampal Subfield Grading For Alzheimer’s Disease Classification

Alzheimer’s Disease Neuroimaging Initiative, Dec 1 2019, In : Scientific reports. 9, 1, 13845.

Research output: Contribution to journalArticle

Open Access
10 Scopus citations

Non-coding variability at the APOE locus contributes to the Alzheimer’s risk

Alzheimer’s Disease Neuroimaging Initiative, Dec 1 2019, In : Nature communications. 10, 1, 3310.

Research output: Contribution to journalArticle

Open Access
5 Scopus citations

Predicting Alzheimer’s disease progression using multi-modal deep learning approach

for Alzheimer’s Disease Neuroimaging Initiative, Dec 1 2019, In : Scientific reports. 9, 1, 1952.

Research output: Contribution to journalArticle

Open Access
30 Scopus citations

Preparing next-generation scientists for biomedical big data: Artificial intelligence approaches

Moore, J. H., Boland, M. R., Camara, P. G., Chervitz, H., Gonzalez, G., Himes, B. E., Kim, D., Mowery, D. L., Ritchie, M. D., Shen, L., Urbanowicz, R. J. & Holmes, J. H., 2019, In : Personalized Medicine. 16, 3, p. 247-257 11 p.

Research output: Contribution to journalReview article

3 Scopus citations

Prioritization of cognitive assessments in Alzheimer's disease via learning to rank using brain morphometric data

Peng, B., Yao, X., Risacher, S. L., Saykin, A. J., Shen, L. & Ning, X., May 2019, 2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 8834618. (2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Prioritizing Amyloid Imaging Biomarkers in Alzheimer’s Disease via Learning to Rank

for the ADNI, Jan 1 2019, Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy - 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Proceedings. Zhu, D., Yan, J., Huang, H., Shen, L., Thompson, P. M., Westin, C-F., Pennec, X., Joshi, S., Nielsen, M., Sommer, S., Fletcher, T. & Durrleman, S. (eds.). Springer, p. 139-148 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11846 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Rapid acceleration of the permutation test via transpositions

Chung, M. K., Xie, L., Huang, S. G., Wang, Y., Yan, J. & Shen, L., Jan 1 2019, Connectomics in NeuroImaging - 3rd International Workshop, CNI 2019, Held in Conjunction with MICCAI 2019, Proceedings. Schirmer, M. D., Chung, A. W., Venkataraman, A., Rekik, I. & Kim, M. (eds.). Springer, p. 42-53 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11848 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Statistical inference on the number of cycles in brain networks

Chung, M. K., Huang, S. G., Gritsenko, A., Shen, L. & Lee, H., Apr 2019, ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, p. 113-116 4 p. 8759222. (Proceedings - International Symposium on Biomedical Imaging; vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Targeted genetic analysis of cerebral blood flow imaging phenotypes implicates the INPP5D gene

Alzheimer's Disease Neuroimaging Initiative, Sep 2019, In : Neurobiology of Aging. 81, p. 213-221 9 p.

Research output: Contribution to journalArticle

3 Scopus citations

The BIN1 rs744373 SNP is associated with increased tau-PET levels and impaired memory

The Alzheimer’s Disease Neuroimaging Initiative (ADNI), Dec 1 2019, In : Nature communications. 10, 1, 1766.

Research output: Contribution to journalArticle

Open Access
8 Scopus citations

Type 2 diabetes mellitus, brain atrophy, and cognitive decline

Moran, C., Beare, R., Wang, W., Callisaya, M., Srikanth, V., Weiner, M., Aisen, P., Petersen, R., Jack, C. R., Jagust, W., Trojanowki, J. Q., Toga, A. W., Beckett, L., Green, R. C., Saykin, A. J., Morris, J., Liu, E., Montine, T., Gamst, A., Thomas, R. G. & 234 others, Donohue, M., Walter, S., Gessert, D., Sather, T., Harvey, D., Kornak, J., Dale, A., Bernstein, M., Felmlee, J., Fox, N., Thompson, P., Schuff, N., Alexander, G., Decarli, C., Bandy, D., Koeppe, R. A., Foster, N., Reiman, E. M., Chen, K., Mathis, C., Cairns, N. J., Taylor-Reinwald, L., Trojanowki, J. Q., Shaw, L., Lee, V. M. Y., Korecka, M., Crawford, K., Neu, S., Foroud, T. M., Potkin, S., Shen, L., Kachaturian, Z., Frank, R., Snyder, P. J., Molchan, S., Kaye, J., Quinn, J., Lind, B., Dolen, S., Schneider, L. S., Pawluczyk, S., Spann, B. M., Brewer, J., Vanderswag, H., Heidebrink, J. L., Lord, J. L., Johnson, K., Doody, R. S., Villanueva-Meyer, J., Chowdhury, M., Stern, Y., Honig, L. S., Bell, K. L., Morris, J. C., Ances, B., Carroll, M., Leon, S., Mintun, M. A., Schneider, S., Marson, D., Griffith, R., Clark, D., Grossman, H., Mitsis, E., Romirowsky, A., Detoledo-Morrell, L., Shah, R. C., Duara, R., Varon, D., Roberts, P., Albert, M., Onyike, C., Kielb, S., Rusinek, H., De Leon, M. J., Glodzik, L., De Santi, S., Doraiswamy, P. M., Petrella, J. R., Coleman, R. E., Arnold, S. E., Karlawish, J. H., Wolk, D., Smith, C. D., Jicha, G., Hardy, P., Lopez, O. L., Oakley, M., Simpson, D. M., Porsteinsson, A. P., Goldstein, B. S., Martin, K., Makino, K. M., Ismail, M. S., Brand, C., Mulnard, R. A., Thai, G., McAdams-Ortiz, C., Womack, K., Mathews, D., Quiceno, M., Diaz-Arrastia, R., King, R., Weiner, M., Martin-Cook, K., Devous, M., Levey, A. I., Lah, J. J., Cellar, J. S., Burns, J. M., Anderson, H. S., Swerdlow, R. H., Apostolova, L., Lu, P. H., Bartzokis, G., Silverman, D. H. S., Graff-Radford, N. R., Parfitt, F., Johnson, H., Farlow, M. R., Hake, A. M., Matthews, B. R., Herring, S., Van Dyck, C. H., Carson, R. E., Macavoy, M. G., Chertkow, H., Bergman, H., Hosein, C., Black, S., Stefanovic, B., Caldwell, C., Robin Hsiung, G. Y., Feldman, H., Mudge, B., Assaly, M., Kertesz, A., Rogers, J., Trost, D., Bernick, C., Munic, D., Kerwin, D., Mesulam, M. M., Lipowski, K., Wu, C. K., Johnson, N., Sadowsky, C., Martinez, W., Villena, T., Turner, R. S., Johnson, K., Reynolds, B., Sperling, R. A., Johnson, K. A., Marshall, G., Frey, M., Yesavage, J., Taylor, J. L., Lane, B., Rosen, A., Tinklenberg, J., Sabbagh, M., Belden, C., Jacobson, S., Kowall, N., Killiany, R., Budson, A. E., Norbash, A., Johnson, P. L., Obisesan, T. O., Wolday, S., Bwayo, S. K., Lerner, A., Hudson, L., Ogrocki, P., Fletcher, E., Carmichael, O., Olichney, J., Kittur, S., Borrie, M., Bartha, D. R., Johnson, S., Asthana, S., Carlsson, C. M., Potkin, S. G., Preda, A., Nguyen, D., Tariot, P., Fleisher, A., Reeder, S., Bates, V., Capote, H., Rainka, M., Scharre, D. W., Kataki, M., Zimmerman, E. A., Celmins, D., Brown, A. D., Pearlson, G. D., Blank, K., Anderson, K., Santulli, R. B., Schwartz, E. S., Sink, K. M., Williamson, J. D., Garg, P., Watkins, F., Ott, B. R., Querfurth, H., Tremont, G., Salloway, S., Malloy, P., Correia, S., Rosen, H. J., Miller, B. L., Mintzer, J., Longmire, C. F., Spicer, K., Finger, E., Rachinsky, I., Drost, D., Pomara, N., Hernando, R., Sarrael, A., Schultz, S. K., Boles Ponto, L. L., Shim, H., Smith, K. E., Relkin, N., Chaing, G., Raudin, L., Smith, A., Fargher, K. & Raj, B. A., Feb 19 2019, In : Neurology. 92, 8, p. E823-E830

Research output: Contribution to journalArticle

11 Scopus citations
2018

A Network-Based Framework for Mining High-Level Imaging Genetic Associations

Liang, H., Meng, X., Chen, F., Zhang, Q., Yan, J., Yao, X., Kim, S., Wang, L., Feng, W., Saykin, A. J., Li, J. & Shen, L., Jan 1 2018, Imaging Genetics. Elsevier Inc., p. 119-134 16 p.

Research output: Chapter in Book/Report/Conference proceedingChapter

A novel SCCA approach via truncated â.," 1-norm and truncated group lasso for brain imaging genetics

Du, L., Liu, K., Zhang, T., Yao, X., Yan, J., Risacher, S. L., Han, J., Guo, L., Saykin, A. J. & Shen, L., Jan 15 2018, In : Bioinformatics. 34, 2, p. 278-285 8 p.

Research output: Contribution to journalArticle

11 Scopus citations