Huey-Miin Hsueh
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Explore the profile of Huey-Miin Hsueh including associated specialties, affiliations and a list of published articles.
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12
Citations
263
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Recent Articles
1.
Hsueh H, Tsai C
BMC Bioinformatics
. 2016 Feb;
17:74.
PMID: 26852017
Background: Gene set analysis (GSA) aims to evaluate the association between the expression of biological pathways, or a priori defined gene sets, and a particular phenotype. Numerous GSA methods have...
2.
Hsu M, Chang Y, Hsueh H
BMC Res Notes
. 2014 Jan;
7:25.
PMID: 24410929
Background: A biomarker is usually used as a diagnostic or assessment tool in medical research. Finding an ideal biomarker is not easy and combining multiple biomarkers provides a promising alternative....
3.
Hsueh H, Zhou D, Tsai C
Gene
. 2012 Dec;
518(1):179-86.
PMID: 23219997
In DNA microarray studies, gene-set analysis (GSA) has become the focus of gene expression data analysis. GSA utilizes the gene expression profiles of functionally related gene sets in Gene Ontology...
4.
Chien C, Chang Y, Hsueh H
Biom J
. 2011 Jan;
53(1):5-18.
PMID: 21259305
Case-control sampling is popular in epidemiological research because of its cost and time saving. In a logistic regression model, with limited knowledge on the covariance matrix of the point estimator...
5.
Lin W, Hsueh H, Chen J
BMC Bioinformatics
. 2010 Jan;
11:48.
PMID: 20100337
Background: Before conducting a microarray experiment, one important issue that needs to be determined is the number of arrays required in order to have adequate power to identify differentially expressed...
6.
Hsueh H, Kuo H, Tsai C
J Biopharm Stat
. 2008 Sep;
18(5):869-82.
PMID: 18781522
An important objective in mass spectrometry (MS) is to identify a set of biomarkers that can be used to potentially distinguish patients between distinct treatments (or conditions) from tens or...
7.
Chen J, Hsueh H, Delongchamp R, Lin C, Tsai C
BMC Bioinformatics
. 2007 Oct;
8:412.
PMID: 17961233
Background: Many researchers are concerned with the comparability and reliability of microarray gene expression data. Recent completion of the MicroArray Quality Control (MAQC) project provides a unique opportunity to assess...
8.
Tsai C, Hsueh H, Chen J
J Biopharm Stat
. 2004 Oct;
14(3):553-73.
PMID: 15468752
Microarray technology allows the measurement of expression levels of a large number of genes simultaneously. There are inherent biases in microarray data generated from an experiment. Various statistical methods have...
9.
Tsai C, Hsueh H, Chen J
Biometrics
. 2004 Feb;
59(4):1071-81.
PMID: 14969487
Testing for significance with gene expression data from DNA microarray experiments involves simultaneous comparisons of hundreds or thousands of genes. If R denotes the number of rejections (declared significant genes)...
10.
Chen J, Delongchamp R, Tsai C, Hsueh H, Sistare F, Thompson K, et al.
Bioinformatics
. 2004 Feb;
20(9):1436-46.
PMID: 14962916
Motivation: A microarray experiment is a multi-step process, and each step is a potential source of variation. There are two major sources of variation: biological variation and technical variation. This...