Joint principal trend analysis for longitudinal high-dimensional data-Reference-Cited by-同舟云学术

Joint principal trend analysis for longitudinal high-dimensional data

Published:2017-07-31 Issue:2 Volume:74 Page:430-438
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biom

Author:

Zhang Yuping¹²³^ORCID,Ouyang Zhengqing⁴⁵⁶

Affiliation:

1. Department of Statistics; University of Connecticut; Storrs, Connecticut U.S.A.

2. Center for Quantitative Medicine; University of Connecticut Health Center; Farmington, Connecticut U.S.A.

3. Institute for Systems Genomics, Institute for Collaboration on Health, Intervention, and Policy, CT Institute of the Brain and Cognitive Sciences; University of Connecticut; Storrs, Connecticut U.S.A.

4. The Jackson Laboratory for Genomic Medicine; Farmington, Connecticut U.S.A.

5. Department of Biomedical Engineering, Institute for Systems Genomics; University of Connecticut; Storrs, Connecticut U.S.A.

6. Department of Genetics and Genome Sciences; University of Connecticut Health Center; Farmington, Connecticut U.S.A.

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/biom.12751/fullpdf

Reference35 articles.

1. Toward understanding and exploiting tumor heterogeneity;Alizadeh;Nature Medicine,2015

2. Maximizing the power of principal-component analysis of correlated phenotypes in genome-wide association studies;Aschard;The American Journal of Human Genetics,2014

3. Balakrishnan , S. Puniyani , K. Lafferty , J. 2012 Sparse additive functional and kernel cca Proceedings of the 29th International Conference on Machine Learning (ICML-12) 911 918

4. Deconvolving cell cycle expression data with complementary information;Bar-Joseph;Bioinformatics,2004

5. Genome-wide transcriptional analysis of the human cell cycle identifies genes differentially regulated in normal and cancer cells;Bar-Joseph;Proceedings of the National Academy of Sciences,2008

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