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Super-sparse principal component analyses for high-throughput genomic data
Donghwan Lee
, Woojoo Lee
, Youngjo Lee
, Yudi Pawitan
Department of Statistics
Research output
:
Contribution to journal
›
Article
›
peer-review
43
Scopus citations
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Computer Science
High Throughput
100%
Component Analysis
100%
Principal Components
100%
Nonzero Coefficient
40%
Singular Value
40%
Least Squares Method
20%
Gene Expression Data
20%
Data Matrix
20%
High Dimensional Data
20%
Small Fraction
20%
Data Application
20%
Linear Combination
20%
Engineering
Component Analysis
100%
Principal Components
100%
Sparse Super
100%
Nonzero Coefficient
40%
Illustrates
20%
Dimensional Data
20%
Singular Value Decomposition
20%
Least Square
20%
Singular Value
20%
Random Effect
20%
Linear Combination
20%
Mathematics
Principal Component Analysis
100%
Matrix (Mathematics)
25%
Singular Value Decomposition
25%
Random Effects Model
25%
Partial Least Squares
25%
Linear Combination
25%
Principal Components
25%
True Vector
25%
Singular Value
25%
Dimensional Data
25%