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  • Li Shen
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

A Review of Statistical-learning Imaging Genetics

Hao, X. K., Li, C. X., Yan, J. W., Shen, L. & Zhang, D. Q., Jan 2018, In : Zidonghua Xuebao/Acta Automatica Sinica. 44, 1, p. 13-24 12 p.

Research output: Contribution to journalReview article

Bootstrapped Sparse Canonical Correlation Analysis: Mining Stable Imaging and Genetic Associations With Implicit Structure Learning. Mining Stable Imaging and Genetic Associations With Implicit Structure Learning.

Yan, J., Du, L., Kim, S., Risacher, S. L., Huang, H., Inlow, M., Moore, J. H., Saykin, A. J. & Shen, L., Jan 1 2018, Imaging Genetics. Elsevier Inc., p. 101-117 17 p.

Research output: Chapter in Book/Report/Conference proceedingChapter

Characteristic patterns of inter- and intra-hemispheric metabolic connectivity in patients with stable and progressive mild cognitive impairment and Alzheimer’s disease

for the Alzheimer’s Disease Neuroimaging Initiative, Dec 1 2018, In : Scientific reports. 8, 1, 13807.

Research output: Contribution to journalArticle

4 Scopus citations

GPU Accelerated Browser for Neuroimaging Genomics

Alzheimer’s Disease Neuroimaging Initiative, Oct 1 2018, In : Neuroinformatics. 16, 3-4, p. 393-402 10 p.

Research output: Contribution to journalArticle

Heritability estimation of reliable connectomic features

Xie, L., Amico, E., Salama, P., Wu, Y. C., Fang, S., Sporns, O., Saykin, A. J., Goñi, J., Yan, J. & Shen, L., Jan 1 2018, Connectomics in NeuroImaging - 2nd International Workshop, CNI 2018, Held in Conjunction with MICCAI 2018, Proceedings. Wu, G., Schirmer, M. D., Chung, A. W., Rekik, I. & Munsell, B. (eds.). Springer Verlag, p. 58-66 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11083 LNCS).

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

1 Scopus citations

Image Registration and Predictive Modeling: Learning the Metric on the Space of Diffeomorphisms

Mussabayeva, A., Kroshnin, A., Kurmukov, A., Denisova, Y., Shen, L., Cong, S., Wang, L. & Gutman, B. A., Jan 1 2018, Shape in Medical Imaging - International Workshop, ShapeMI 2018, Held in Conjunction with MICCAI 2018, Proceedings. Lombaert, H., Paniagua, B., Egger, B., Lüthi, M., Reuter, M. & Wachinger, C. (eds.). Springer Verlag, p. 160-168 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11167 LNCS).

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

1 Scopus citations

Imaging genomics

Huang, H., Shen, L., Thompson, P. M., Huang, K., Huang, J. & Yang, L., 2018, In : Pacific Symposium on Biocomputing. 0, 212669, p. 304-306 3 p.

Research output: Contribution to journalConference article

2 Scopus citations

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

Yan, J., Liu, K., Lv, H., Amico, E., Risacher, S. L., Wu, Y. C., Fang, S., Sporns, O., Saykin, A. J., Goni, J. & Shen, L., May 23 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. IEEE Computer Society, p. 6-9 4 p. (Proceedings - International Symposium on Biomedical Imaging; vol. 2018-April).

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

Joint high-order multi-task feature learning to predict the progression of Alzheimer’s disease

ADNI, Jan 1 2018, Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings. Schnabel, J. A., Davatzikos, C., Alberola-López, C., Fichtinger, G. & Frangi, A. F. (eds.). Springer Verlag, p. 555-562 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11070 LNCS).

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

4 Scopus citations

Longitudinal genotype-phenotype association study through temporal structure auto-learning predictive model

Wang, X., Yan, J., Yao, X., Kim, S., Nho, K., Risacher, S. L., Saykin, A. J., Shen, L. & Huang, H., Jul 2018, In : Journal of Computational Biology. 25, 7, p. 809-824 16 p.

Research output: Contribution to journalArticle

2 Scopus citations

Mixture drug-count response model for the high-dimensional drug combinatory effect on myopathy

Wang, X., Zhang, P., Chiang, C. W., Wu, H., Shen, L., Ning, X., Zeng, D., Wang, L., Quinney, S. K., Feng, W. & Li, L., Feb 20 2018, In : Statistics in Medicine. 37, 4, p. 673-686 14 p.

Research output: Contribution to journalArticle

4 Scopus citations

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

Liu, K., Wang, H., Risacher, S., Saykin, A. & Shen, L., May 23 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. IEEE Computer Society, Vol. 2018-April. p. 1402-1405 4 p.

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

3 Scopus citations

Pattern Discovery from High-Order Drug-Drug Interaction Relations

Chiang, W. H., Schleyer, T., Shen, L., Li, L. & Ning, X., Sep 1 2018, In : Journal of Healthcare Informatics Research. 2, 3, p. 272-304 33 p.

Research output: Contribution to journalArticle

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

Lu, L., Wang, H., Yao, X., Risacher, S., Saykin, A. & Shen, L., May 23 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. IEEE Computer Society, Vol. 2018-April. p. 545-548 4 p.

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

2 Scopus citations

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

Wang, X., Chen, H., Yan, J., Nho, K., Risacher, S. L., Saykin, A. J., Shen, L. & Huang, H., Sep 1 2018, In : Bioinformatics. 34, 17, p. i866-i874

Research output: Contribution to journalArticle

1 Scopus citations

Translational High-Dimensional Drug Interaction Discovery and Validation Using Health Record Databases and Pharmacokinetics Models

Chiang, C. W., Zhang, P., Wang, X., Wang, L., Zhang, S., Ning, X., Shen, L., Quinney, S. K. & Li, L., Feb 2018, In : Clinical Pharmacology and Therapeutics. 103, 2, p. 287-295 9 p.

Research output: Contribution to journalArticle

13 Scopus citations

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The Genetic FTD Initiative (GENFI) & The Alzheimer’s Disease Neuroimaging Initiative (ADNI), Dec 1 2018, In : Nature communications. 9, 1, 4273.

Research output: Contribution to journalArticle

33 Scopus citations

Volumetric comparison of hippocampal subfields extracted from 4-minute accelerated vs. 8-minute high-resolution T2-weighted 3T MRI scans

Cong, S., Risacher, S. L., West, J. D., Wu, Y. C., Apostolova, L. G., Tallman, E., Rizkalla, M., Salama, P., Saykin, A. J. & Shen, L., Dec 1 2018, In : Brain Imaging and Behavior. 12, 6, p. 1583-1595 13 p.

Research output: Contribution to journalArticle

3 Scopus citations
2017

A fast SCCA algorithm for big data analysis in brain imaging genetics

Alzheimer’s Disease Neuroimaging Initiative, 2017, Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - 1st International Workshop, GRAIL 2017 6th International Workshop, MFCA 2017 and 3rd International Workshop, MICGen 2017 Held in Conjunction with MICCAI 2017, Proceedings. Springer Verlag, Vol. 10551 LNCS. p. 210-219 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10551 LNCS).

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

1 Scopus citations