Shin-Han Shiu was trained as a microbiologist during his undergraduate years and went on to study receptor biochemistry in University of Wisconsin for his PhD. During the latter part of his PhD years in late 90s, multiple genome projects started, and Shin-Han started to be fascinated with evolution and genome biology questions, and particularly how computational approaches could be used to resolve them. Armed with an interest in the application of computation in biology and in evolution, Shin-Han went on to be a postdoctoral scientist in Institute of Bioinformatics, Helmholtz Zentrum München (then GSF), Germany to learn more about computational biology; and an NIH National Research Service Award Fellow in University of Chicago to gain a better understanding of evolutionary processes.
Since arriving in Michigan State University in 2006, his laboratory has focused on understanding how genome function and evolve, as well as how computational modeling and quantitative approaches can be used to answer biological questions.
Ph.D., Department of Botany, University of Wisconsin-Madison, 1994-2001
B.S., Department of Plant Pathology, National Taiwan University, Taiwan, 1988-1992
Professor, Department of Computational Math, Sci, & Engr., Michigan State University, 2018-present
Associate Director, Genetics Graduate Program, Michigan State University, 2017-present
Professor, Department of Plant Biology, Michigan State University, 2017-present
Visiting Associate Scholar, Biodiversity Center, Academia Sinica, Taiwan, 2012
Associate Professor, Department of Plant Biology, Michigan State University, 2011-2017
Assistant Professor, Department of Plant Biology, Michigan State University, 2006-2011
NIH NRSA Fellow, Department of Ecology and Evolution, University of Chicago, 2002-2005
Postdoctoral scientist, Inst. for Bioinformatics, Helmholtz Zentrum München, Germany, 2002
- Molecular evolution: How do gene functions evolve after duplication? What are the factors/mechanisms contribute to duplicate retention? To what extent do environmental responses diverge within and between species? How does such response divergence contribute to adaptation? What are the molecular mechanisms underlying divergence in environmental response?
- Molecular regulatory model: What are the major factors influencing transcriptional regulation under diverse environmental conditions? How may we integrate these factors to establish computational models predictive of gene expression in a spatial, temporal, and condition-specific manner?
- Defining functional genomic regions through modeling: What is the evolutionary significance of a measurable biochemical activity in a cell? Particularly, what is the significance of expression in “intergenic” space? How may we integrate functional and comparative genomic data to define functional regions?
- Predicting phenotypes: How may we integrate genotype information, functional genomic data, and physiological measurements to predict molecular functions, physiological response, and morphological characteristics under a particular environment?