News & Updates
Find A Specialist
Resource Finder at Kennedy Krieger Institute
A free resource that provides access to information and support for individuals and families living with developmental disabilities.
Jonathan Pevsner, Ph.D.
Dr. Jonathan Pevsner is a research scientist at the Kennedy Krieger Institute. He also holds a primary faculty appointment in the Department of Psychiatry and Behavioral Sciences at the Johns Hopkins University School of Medicine.
Dr. Pevsner received his bachelor's degree in psychology from Haverford College and his doctoral degree in pharmacology and molecular sciences from the Johns Hopkins School of Medicine. He pursued post-doctoral training at the Stanford University School of Medicine, and joined the faculty of Kennedy Krieger Institute in 1995.
Dr. Pevsner studies the molecular basis of childhood brain disorders. The diseases we study include autism, Rett syndrome, and Down syndrome. For studies of human brain disorders, we perform gene expression profiling to identify disease markers and to search for biochemical pathways that have been disturbed in brain or peripheral cells from patients.
The Pevsner Lab is involved in bioinformatics research. Bioinformatics is the interface between molecular biology and computers. The lab has developed the following programs:  "Database Referencing of Array Genes ONline" (DRAGON), a web-accessible database that helps researchers analyze the data obtained from microarrays or other gene expression experiments. Once a microarray experiment indicates the expression levels of tens of thousands of genes, researchers must identify the biological characteristics associated with all of those genes and their encoded proteins. Looking online for information about each gene individually is time-consuming and impractical. DRAGON compiles information from a variety of public databases. It then rapidly supplies information pertaining to a range of the biological characteristics of the genes in any microarray data set.  "Standardization and Normalization of Microarray Data" (SNOMAD), a set of web-accessible tools for the analysis of genes that are significantly regulated in microarray data sets. SNOMAD includes non-linear transformations to correct for bias and variance in array data.  "Statistical Analysis and Visualization of Annotated Gene Expression data" (SAVAGE), a data visualization tool that uses principal components analysis to graphically display functionally annotated gene expression data sets.