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Richard H. Scheuermann, PhD, is the director of the La Jolla Campus at the J. Craig Venter Institute (JCVI) and an adjunct professor of pathology at U.C. San Diego. He received a BS in Life Sciences from the Massachusetts Institute of Technology, and a PhD in Molecular Biology from the University of California, Berkeley. After completing his doctoral research, he accepted an independent research position at the Basel Institute for Immunology in Basel, Switzerland. In 1992, he joined the faculty in the Department of Pathology at the University of Texas Southwestern Medical Center in Dallas where he rose to the rank of Professor with tenure. In 2001, he made a career shift into the discipline of bioinformatics, initiated with a sabbatical year at the San Diego Supercomputer Center. In 2012, Dr. Scheuermann moved to San Diego to become the Director of Informatics at JCVI, and in 2016 was promoted to Director of the La Jolla Campus.

Dr. Scheuermann has applied his deep knowledge in molecular immunology and infectious disease toward the development of novel computational data mining methods and knowledge representation approaches, including the development of biomedical ontologies and their use in data mining, novel methods for the analysis of gene expression, protein network and flow cytometry data, and novel comparative genomics methods. These computational methods have been made available through several public database and analysis resources, including the Influenza Research Database (IRD), the Virus Pathogen Resource (ViPR), and the Immunology Database and Analysis Portal (ImmPort) supported by the U.S. National Institutes of Health.

Research Priorities

Informatics database resources and knowledge representation standards

  • Principle investigator on the Influenza Research Database (IRD), the Virus Pathogen Resource (ViPR) and the Immunology Database and Analysis Portal (ImmPort) development projects.
  • Development of biomedical ontologies and other knowledge representation standards through the Open Biomedical Ontology (OBO) Foundry, including the Cell Ontology (CL), the Ontology for General Medical Sciences (OGMS), the Ontology for Biomedical Investigations (OBI), and the Minimum Information about a Flow Cytometry Experiment (MIFlowCyt).

Flow cytometry analysis methods

  • Development of a suite of cytometry data processing and analysis methods, including FLOCK, FlowMap-FR, FCSTrans, and DAFi.
  • Co-founder of the FlowCAP Consortium for the critical evaluation of cytometry analysis methods using benchmark datasets and objective performance metrics.
  • Development of the FlowGate resource for user-friendly access to cytometry analysis methods.
  • Application of computational cytometry analysis methods to study immunological responses to vaccination, respiratory pathogen infection, autoimmunity, and leukemia and lymphoma.

Systems biology analysis methods

  • Identification of functional modules within gene/protein networks based on their topological properties using MoNet and dMoNet.
  • Dissemination of systems biology of infectious diseases data through the IRD and ViPR resources.

Transcriptomics and single cell genomics

  • Development of a suite of gene expression microarray analysis methods, including DFW, DFCM, CLASSIFI, and GO-Bayes.
  • Use of single cell RNA sequencing (scRNAseq) to study the cellular complexity of the human cerebral cortex, vaccine responses, and the development of multiple sclerosis.
  • Application of machine learning methods for scRNAseq analysis, including quality control procedures and marker gene feature selection.


Select Publications

Fast and accurate HLA typing from short-read next-generation sequence data with xHLA.
Proceedings of the National Academy of Sciences of the United States of America. 2017-07-25; 114.30: 8059-8064.
PMID: 28674023
Mapping cell populations in flow cytometry data for cross-sample comparison using the Friedman-Rafsky test statistic as a distance measure.
Cytometry. Part A : the journal of the International Society for Analytical Cytology. 2016-01-01; 89.1: 71-88.
PMID: 26274018
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 2016-01-01; 22.564-575.
PMID: 27897007
Critical assessment of automated flow cytometry data analysis techniques.
Nature methods. 2013-03-01; 10.3: 228-38.
PMID: 23396282
Elucidation of seventeen human peripheral blood B-cell subsets and quantification of the tetanus response using a density-based method for the automated identification of cell populations in multidimensional flow cytometry data.
Cytometry. Part B, Clinical cytometry. 2010-01-01; 78 Suppl 1.S69-82.
PMID: 20839340