Ji-Ping Wang
Assistant Professor of Statistics
Ph.D., 2003, Pennsylvania State University
Research Interests
My research has two areas: (1) mixture model, computing algorithms and
applications; (2) bioinformatics and computational biology. Mixture models
provide a flexible and powerful modeling tool to a wide variety of
applications. My recent work concerns how to improve the nonparametric
maximum likelihood estimation (NPMLE) using penalized likelihood method in
important applications including species richness estimation. My research in
bioinformatics and computational biology aims to develop complex statistical
methods to high throughput genomic and genetic data. The current working
projects include Expressed Sequence Tag (EST) data analysis, nucleosome
sequence alignment and positioning prediction, human braining mapping, DNA
methylation differentiation and tRNA inter-positional association. Some
software tools developed including ESTstat (EST), NuPoP (nucleosome) and
SPECIES (species number estimation) are freely available at my personal
Recent Publications
A penalized nonparametric maximum likelilhood approach to species richness estimation (with Linday, B.), Journal of American Statistical Association, 2005,100(471):942-959.
Improved alignment of nucleosome DNA sequences using a mixture model(with Widom, J.), Nucleic Acids Research, 2005, 33(21):6743-6755 2005.
A genomic code for nucleosome positioning (with Segal, E.,Widom, J. et al) Nature, 2006, 442(7104):719-846.
Some optimization results and a VDM/ECM algorithm for penalized and constrained nonparametric maximum likelihood estimation for mixtures, Computational Statistics and Data Analysis, 2007, 51:2946-2957.
More Information
Personal website: http://bioinfo.stats.northwestern.edu/~jzwang/
