Y
Yee Hwa Yang
Researcher at University of Sydney
Publications - 63
Citations - 10054
Yee Hwa Yang is an academic researcher from University of Sydney. The author has contributed to research in topics: Gene expression & Gene expression profiling. The author has an hindex of 33, co-authored 60 publications receiving 9733 citations. Previous affiliations of Yee Hwa Yang include University of California, Berkeley & Helen Wills Neuroscience Institute.
Papers
More filters
Journal ArticleDOI
Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation
TL;DR: This article proposes normalization methods that are based on robust local regression and account for intensity and spatial dependence in dye biases for different types of cDNA microarray experiments.
Journal ArticleDOI
Design issues for cDNA microarray experiments.
Yee Hwa Yang,Terence P. Speed +1 more
TL;DR: This paper focuses on microarray experiments, which are used to quantify and compare gene expression on a large scale and can be costly in terms of equipment, consumables and time.
Journal ArticleDOI
Genome-wide profiling identifies epithelial cell genes associated with asthma and with treatment response to corticosteroids
Prescott G. Woodruff,Homer A. Boushey,Gregory Dolganov,Christopher S. Barker,Yee Hwa Yang,Samantha Donnelly,Almut Ellwanger,Sukhvinder Sidhu,Trang Dao-Pick,Carlos R. Pantoja,David J. Erle,Keith R. Yamamoto,John V. Fahy +12 more
TL;DR: The findings show that airway epithelial cells in asthma have a distinct activation profile and identify direct and cell-autonomous effects of corticosteroid treatment on airway endothelial cells that relate to treatment responses and can now be the focus of specific mechanistic studies.
Journal ArticleDOI
Comparison of Methods for Image Analysis on cDNA Microarray Data
TL;DR: New addressing, segmentation, and background correction methods for extracting information from microarray scanned images are proposed and it is suggested that seeded region growing segmentation with morphological background correction provides precise and accurate estimates of foreground and background intensities.
Book ChapterDOI
Statistical issues in cDNA microarray data analysis.
TL;DR: Statistical considerations are frequently to the fore in the analysis of microarray data, as researchers sift through massive amounts of data and adjust for various sources of variability in order to identify the important genes amongst the many which are measured.