High throughput experimental methodologies are generating large volumes of data at an unprecedented rate. The challenge now is to extract biological knowledge from these massive data sets. One of the major themes in our group is to develop and use bioinformatics systems and computational biology approaches to support data mining in order to develop hypotheses about how biological systems work, and then to test these hypotheses using directed wet lab experimentation in translational research projects focused on disease pathogenesis.
In the wet lab, our group is focused on understanding the molecular and cellular responses to the activation of signal transduction pathways in lymphocytes. We are especially interested in understanding how external stimulation affects normal B cell homeostasis and function, especially antigen processing and presentation and lymphocyte survival, and the pathogenesis of autoimmune disease and B cell neoplasia.
Our group is also currently developing two large biomedical database systems for the National Institute of Allergy and Infectious Disease (NIAID). The BioHealthBase (www.biohealthbase.org ) is being developed to support research data relevant to select Category A ? C pathogens as defined by the CDC, including influenza virus, Mycobacterium tuberculosis and Francisella tularensis. The BioHealthBase currently contains integrated data sets regarding gene and protein structure and function from NCBI, UniProt, Pfam, BioCyc and other sources, and system-generated data regarding predicted operon structures, protein localization, epitope structure and polymorphism locations. The Immunology Database and Analysis Portal (www.immport.org ) is being developed to provide advanced information technology support in the production, analysis, archiving, exchange and integration of genomic, proteomic and related research data from NIAID-funded investigators working on basic scientific research of immune system development and function, genetic determinants of immune disease, and clinical trials to evaluate the safety, toxicity, and efficacy of immune disease therapies.
Our current computational biology projects include the development and validation of data analysis approaches that combine gene expression microarray data with Gene Ontology functional annotation (http://pathcuric1.swmed.edu/pathdb/classifi.html ), the development and validation of automated approaches for the modular decomposition of biological networks based on measures of network topology, nonparametric modeling of Affymetrix microarray data to improve data preprocessing, and the development and validation of automated population identification using grid-based clustering approaches for multidimensional flow cytometry data.
RESEARCH INTERESTS
Signal transduction in the control of lymphocyte growth, development and function
Bioinformatic database development for infectious disease, biodefense and immunology research
Development of new computational tools for large scale data analysis
RECENT PUBLICATIONS
Zhongxue Chen, Monnie McGee, Qingzhong Liu and Richard H. Scheuermann, "Distribution Free Summarization Method for Affymetrix GeneChip Arrays" Bioinformatics, 23:321-327, 2007
Feng Luo, Yunfeng Yang, Chin-Fu Chen, Roger Chang, Jizhong Zhou and Richard H. Scheuermann, "Modular organization of protein interaction networks" Bioinformatics, 23:207-214, 2007
Alexander D. Diehl, Jamie A. Lee, Richard H. Scheuermann, and Judith A. Blake, "Ontology development for biological systems: Immunology" Bioinformatics, 23:913-915, 2007
Jamie A. Lee, Robert Sinkovits, Dennis Mock, Eva Rab, Jennifer Cai, Peng Yang, Eva Rab, Brian Saunders, Robert C. Hsueh, Sangdun Choi, Shankar Subramaniam and Richard H. Scheuermann, "Components of the antigen processing and presentation pathway revealed by gene expression microarray analysis following B cell antigen receptor (BCR) stimulation" BMC Bioinformatics, 7:237, 2006
John M. Greene, Frank Collins, Elliot J. Lefkowitz, David Roos, Richard H. Scheuermann, Bruno Sobral, Rick Stevens, Owen White, and Valentina Di Francesco, "NIAID Bioinformatics Resource Centers - New Assets for Pathogen Informatic" Infection and Immunity, 75:3212-3219, 2007
SIGNIFICANT PUBLICATIONS
Xin Bai, Beverly Barton Rogers, Paul C. Harkins, John Sommerauer, Robert Squires, Kathleen Rotondo, Albert Quan, D. Brian Dawson and Richard H. Scheuermann, "Predictive value of quantitative PCR-based viral burden analysis for eight human herpesviruses in pediatric solid organ transplant patients" Journal of Molecular Diagnostics, 2:191-201, 2000
Gregory A. Hosler, Robert Bash and Richard H. Scheuermann, "Kinetics of early therapeutic response as measured by quantitative PCR predicts survival in a murine xenograft model of human T-cell acute lymphoblastic leukemia" Leukemia, 14:1215-1224, 2000
Gilman AG, Simon MI, Bourne HR, Harris BA, Long R, Ross EM, Stull JT, Taussig R, Bourne HR, Arkin AP, Cobb MH, Cyster JG, Devreotes PN, Ferrell JE, Fruman D, Gold M, Weiss A, Stull JT, Berridge MJ, Cantley LC, Catterall WA, Coughlin SR, Olson EN, Smith TF, Brugge JS, Botstein D, Dixon JE, Hunter T, Lefkowitz RJ, Pawson AJ, Sternberg PW, Varmus H, Subramaniam S, Sinkovits RS, Li J, Mock D, Ning Y, Saunders B, Sternweis PC, Hilgemann D, Scheuermann RH, DeCamp D, Hsueh R, Lin KM, Ni Y, Seaman WE, S, "Overview of the alliance for cellular signalling" Nature, 420:703-706, 2002
Jonathan W. Uhr, Richard H. Scheuermann, Nancy E. Street and Ellen S. Vitetta, "Cancer dormancy: Opportunities for new therapeutic approaches" Nature Medicine, 3:505-509, 1997
Richard H. Scheuermann, Emilian Racila, Thomas F. Tucker, Eitan Yefenof, Nancy E. Street, Ellen S. Vitetta, Louis J. Picker and Jonathan W. Uhr, "Lyn tyrosine kinase signals cell cycle arrest but not apoptosis in B-lineage lymphoma cells" Proceedings of the National Academy of Sciences USA, 91:4048-4052, 1994
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