Data Analysis

BIOSTATISTICS RESOURCE

Recent advances in large-scale mRNA expression measurements and proteomic technologies have opened the opportunity for massively parallel biological data acquisition and thus have shifted our attention towards an integrated understanding of the genetic networks underlying complex biological phenotypes. Despite many statistical developments for genomics research over the past several years, some basic statistical questions have not been very well addressed primarily because a very large number of genes are studied with a limited number of replicates. Therefore, it is not a trivial task to identify genes with different expression levels across a set of samples and to identify genes with correlated expression patterns. It is even more challenging to understand biological pathways from microarray data and to integrate data of various types.

The Biostatistics Resources provides state-of-the-art statistical analyses to identify genes with different expression levels among a set of conditions, to cluster genes with co-regulated expression patterns, and to identify biomarkers from microarray data for disease diagnosis and prognosis. In addition to providing basic biostatistics services, we are collaborating with the Microarray Resource and with many research labs which are conducting large scale gene expression experiments. We are also part of the Yale Microarray Database. For statistical and computational methodology developments, we are (1) developing statistical methods to estimate gene expression level changes among a set of samples and to identify genes with different expression levels for both cDNA microarrays and Affymetrix microarrays; (2) developing novel approaches for the analysis of clustering; and (3) developing computational and visualization tools to dissect biological pathways. Our active methodology and collaborative research programs will ensure that we will be able to provide the most powerful statistical methods to extract as much information as possible from microarray experiments.

Service Charges

Other Useful Links

Publications

Staff
Hongyu Zhao
Aiping Lin
Ji Young Le