|
Dr. Hsiung’s current
research interests include statistical genetics and genetic
epidemiology. Her laboratory also puts efforts on microarray
analysis for gene expression data and array CGH data. Her work
is to use statistical approach to help solve biomedical problems
and to develop statistical methodologies for problems rising
from real biomedical applications.
Research Activities
Dr. Hsiung has authored
over 90 original research articles. She has been a reviewer for
many journals. She was elected as a fellow in the Institute of
Mathematical Statistics, also an elected member of International
Statistical Institutes.
Dr. Hsiung has hosted and
organized many national and international meetings and symposia
including, most recently serving as the program chair for “ the
5th Cross-Strait Conference on Statistics and
Probability”.
Dr. Hsiung has worked on
the topic of event history analysis, including Cox regression
model, generalized proportional hazards models and frailty
models etc. which have wide applications in biomedical research.
After Dr. Hsiung joined NHRI, she and her research team have
been participating in an international genetic study---Stanford
Asia Pacific program in Hypertension and Insulin Resistance (SAPPHIRe).
Collaborating with several medical centers in Taiwan, Hawaii and
San Francisco Bay Area, they have successfully recruited over
1250 sib pairs. Many clinical and environmental data were
collected and analyzed. They have published papers on study of
the association between hypertension/metabolic syndrome and
polymorphisms for several important candidate genes. They also
published results on linkage analysis for quantitative traits
related to metabolic syndrome based on the genome-wide scan
data. The second wave and the third wave of the follow-up study
has mainly been coordinated by Dr. Hsiung’s team .
With the above experience,
Dr. Hsiung has launched the Genetic Epidemiological Study of
Female Lung Adenocarcinoma (GEFLAC) in Taiwan by collaborating
with six hospitals and epidemiologists at National Taiwan
University. Over 4000 cases and controls have been recruited.
Studies are ongoing and data are being analyzed.
In order to increase the
power of the linkage tests, the team has proposed an
allele-sharing based multipoint linkage test that utilizes
nonparametrically the additional endophenotypes/intermediate
phenotypes. It is shown that the gain in power is influenced by
the correlation between the endophenotype and the phenotype of
main interest. Our method also provides an index to indicate the
relevance of the endophenotypes（Gene.
Epid. 2006）.
For the
segregation analysis, nonparametic estimate
in the Cox-gene model with age-of-onset as phenotype was
proposed
(Bernoulli. 2005),
together with a fast algorithm.
Dr. Hsiung’s research team
also collaborates with investigators on microarray study design,
gene expression data analysis and array-CGH data analysis. Our
newly developed data analysis method to detect DNA copy number
aberations for array-CGH data is based on Bayes regression
approach, which has been verified by real time PCR experiments
indicating that our method outperforms other previously
published methods. Our laboratory has served as a bioinformatics
core for many microarray studies. The constructed microarray
platform has been utilized to conduct various experiments
designed to answer distinct biological questions.
|
