Principal Areas of Teaching and Research

Dr. Chen's research mainly focuses on bioinformatics, especially in developing statistical methods and algorithms for functional genomic data. Her research interests are in the following fields. Phylogeny Program Dr. Chen's lab has developed two programs for phylogeny reconstruction. The  MixtureTree, proposed by Chen, Lindsay and Rosenberg, is a Linux based program (written in C++) which implements an algorithm based on mixture models for reconstructing phylogeny from DNA sequence data. The  MixtureTree Annotator, proposed by Chen and Ogata, is a Java-based program that allows the user an enhanced visualization of the phylogenetic tree generated by MixtureTree by providing the ability to color the resulting tree, and annotate the resulting tree with mutation and coalescent time information. Genometrics The term "genometrics" is invented by Dr. Bruce Lindsay at Penn State. It is to understand the genome functions of difference species. Mixture Models The descendant's DNA population is a mixture of parental DNA populations. To understand the mixture of populations, mixture models is a reasonable approach to those studies in biological data analysis. Data Mining Our focus is to apply association rules which traditionally come from market basket analysis to microarray data with the intent to find descriptive and predictive biological processes. The package developed by Chen et al was written in Matlab for mining association rules for gene expression data analysis. The datasets and package can be downloaded in the download page. Neuron Spike Trend Study To understand potential encoding mechanism of motor cortical neurons for control commands during reach-to-grasp movements, experiments to record neuronal activities have been conducted in many research laboratories. We propose to consider neural firing counts and temporal intervals respectively and apply intergrated Poisson Regression model to categorize different neural activities. Dr. Chen's past publications involved with the development of mixture models for clustering high dimensional sequences, its related theoretical justifications and applications. She also published papers in analysis of election data and DNA sequences' matching probability.