Richard H. Scheuermann is adjunct faculty at the J. Craig Venter Institute. 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.
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.
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.
Nature genetics. 2023-11-09;
Bioinformatics (Oxford, England). 2023-10-03; 39.10:
Nature immunology. 2023-10-01; 24.10: 1616-1627.
Nature immunology. 2023-10-01; 24.10: 1778.
The Journal of investigative dermatology. 2023-08-19;
Cross-Comparison of Inflammatory Skin Disease Transcriptomics Identifies PTEN as a Pathogenic Disease Classifier in Cutaneous Lupus Erythematosus
PLoS biology. 2023-06-30; 21.6: e3002133.
Cell reports. Medicine. 2023-06-20; 4.6: 101088.
Scientific reports. 2023-06-13; 13.1: 9567.
Reference-based cell type matching of in situ image-based spatial transcriptomics data on primary visual cortex of mouse brain
Vaccine. 2023-05-11; 41.20: 3171-3177.
Emerging infectious diseases. 2023-05-01; 29.5:
Scientific data. 2023-04-28; 10.1: 246.
Scientific data. 2023-01-24; 10.1: 50.
Nucleic acids research. 2023-01-06; 51.D1: D678-D689.
Introducing the Bacterial and Viral Bioinformatics Resource Center (BV-BRC): a resource combining PATRIC, IRD and ViPR
Cell host & microbe. 2022-12-14; 30.12: 1662-1670.e4.
Defining antigen targets to dissect vaccinia virus and monkeypox virus-specific T cell responses in humans
Frontiers in bioinformatics. 2022-10-24; 2.1020189.
Bioinformatics (Oxford, England). 2022-10-14; 38.20: 4735-4744.
Scientific reports. 2022-10-06; 12.1: 16731.
A novel vaccine based on SARS-CoV-2 CD4+ and CD8+ T cell conserved epitopes from variants Alpha to Omicron
PloS one. 2022-09-23; 17.9: e0275070.
Journal of virology. 2022-08-10; 96.15: e0083322.
Scientific reports. 2022-06-15; 12.1: 9996.
Virology. 2022-05-01; 570.123-133.
Nature. 2022-05-01; 605.7911: 640-652.
Nature. 2022-04-01; 604.7904: E8.
Science translational medicine. 2022-03-02; 14.634: eabn7842.
Antibodies elicited by SARS-CoV-2 infection or mRNA vaccines have reduced neutralizing activity against Beta and Omicron pseudoviruses
Plant physiology. 2022-02-04; 188.2: 879-897.
The genome and preliminary single-nuclei transcriptome of Lemna minuta reveals mechanisms of invasiveness
Journal of leukocyte biology. 2021-12-01; 110.6: 1225-1239.
Corticosteroid treatment in COVID-19 modulates host inflammatory responses and transcriptional signatures of immune dysregulation
Frontiers in immunology. 2021-10-29; 12.690470.
Machine Learning-Based Single Cell and Integrative Analysis Reveals That Baseline mDC Predisposition Correlates With Hepatitis B Vaccine Antibody Response
Nature. 2021-10-06; 598.7879: 111-119.
Genome research. 2021-10-01; 31.10: 1767-1780.
A machine learning method for the discovery of minimum marker gene combinations for cell type identification from single-cell RNA sequencing
Cell reports. Medicine. 2021-07-20; 2.7: 100355.
Impact of SARS-CoV-2 variants on the total CD4+ and CD8+ T cell reactivity in infected or vaccinated individuals
Briefings in bioinformatics. 2021-07-20; 22.4:
FR-Match: robust matching of cell type clusters from single cell RNA sequencing data using the Friedman-Rafsky non-parametric test
Database : the journal of biological databases and curation. 2021-07-09; 2021.
Nature medicine. 2021-05-01; 27.5: 892-903.
JCI insight. 2021-04-08; 6.7:
A system-view of Bordetella pertussis booster vaccine responses in adults primed with whole-cell versus acellular vaccine in infancy
Nature neuroscience. 2021-04-01; 24.4: 612.
Author Correction: A community-based transcriptomics classification and nomenclature of neocortical cell types
Nature neuroscience. 2021-04-01; 24.4: 613.
Publisher Correction: A community-based transcriptomics classification and nomenclature of neocortical cell types
bioRxiv : the preprint server for biology. 2021-03-01;
Negligible impact of SARS-CoV-2 variants on CD4 + and CD8 + T cell reactivity in COVID-19 exposed donors and vaccinees
Lancet (London, England). 2021-01-23; 397.10271: 334-346.
Nature biotechnology. 2020-12-01; 38.12: 1384-1386.
Nature neuroscience. 2020-12-01; 23.12: 1456-1468.
Frontiers in immunology. 2020-11-30; 11.578801.
Multi-Omic Data Integration Allows Baseline Immune Signatures to Predict Hepatitis B Vaccine Response in a Small Cohort
Microorganisms. 2020-11-25; 8.12:
Frontiers in immunology. 2020-11-04; 11.580373.
Systems Biology Methods Applied to Blood and Tissue for a Comprehensive Analysis of Immune Response to Hepatitis B Vaccine in Adults
medRxiv : the preprint server for health sciences. 2020-10-27;
Vaccine: X. 2020-08-07; 5.100065.
Unbiased analysis of peripheral blood mononuclear cells reveals CD4 T cell response to RSV matrix protein
Proceedings of the National Academy of Sciences of the United States of America. 2020-06-09; 117.23: 12522-12523.
Sampling bias and incorrect rooting make phylogenetic network tracing of SARS-COV-2 infections unreliable
Cell host & microbe. 2020-04-08; 27.4: 671-680.e2.
A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2
Nature communications. 2020-03-03; 11.1: 1172.
Transcriptomic evidence that von Economo neurons are regionally specialized extratelencephalic-projecting excitatory neurons
Cytometry. Part A : the journal of the International Society for Analytical Cytology. 2020-03-01; 97.3: 296-307.
Human immunology. 2019-11-01; 80.11: 923-929.
A survey of known immune epitopes in the enteroviruses strains associated with acute flaccid myelitis
Nature. 2019-09-01; 573.7772: 61-68.
JCI insight. 2019-05-02; 4.9:
Virology. 2019-03-01; 529.29-42.
Classification of human Herpesviridae proteins using Domain-architecture Aware Inference of Orthologs (DAIO)
Methods in molecular biology (Clifton, N.J.). 2019-01-01; 1911.47-69.
PloS one. 2018-12-26; 13.12: e0209648.
mBio. 2018-10-16; 9.5:
Contemporary Circulating Enterovirus D68 Strains Have Acquired the Capacity for Viral Entry and Replication in Human Neuronal Cells
Blood advances. 2018-10-09; 2.19: 2419-2429.
Chromosome Y-encoded antigens associate with acute graft-versus-host disease in sex-mismatched stem cell transplant
Nature neuroscience. 2018-09-01; 21.9: 1185-1195.
Transcriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type
Cytometry. Part A : the journal of the International Society for Analytical Cytology. 2018-06-01; 93.6: 597-610.
DAFi: A directed recursive data filtering and clustering approach for improving and interpreting data clustering identification of cell populations from polychromatic flow cytometry data
Viruses. 2018-05-14; 10.5:
Frontiers in immunology. 2018-05-08; 9.976.
VDJServer: A Cloud-Based Analysis Portal and Data Commons for Immune Repertoire Sequences and Rearrangements
Human molecular genetics. 2018-05-01; 27.R1: R40-R47.
The Journal of allergy and clinical immunology. 2018-02-01; 141.2: 775-777.e6.
BMC bioinformatics. 2017-12-21; 18.Suppl 17: 559.
Clinics in laboratory medicine. 2017-12-01; 37.4: 931-944.
BMC bioinformatics. 2017-10-11; 18.1: 448.
Proceedings of the National Academy of Sciences of the United States of America. 2017-07-25; 114.30: 8059-8064.
Nucleic acids research. 2017-01-04; 45.D1: D466-D474.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 2017-01-01; 22.564-575.
PRODUCTION OF A PRELIMINARY QUALITY CONTROL PIPELINE FOR SINGLE NUCLEI RNA-SEQ AND ITS APPLICATION IN THE ANALYSIS OF CELL TYPE DIVERSITY OF POST-MORTEM HUMAN BRAIN NEOCORTEX
Virus evolution. 2016-06-15; 2.1: vew015.
Genetic changes found in a distinct clade of Enterovirus D68 associated with paralysis during the 2014 outbreak
PloS one. 2016-04-29; 11.4: e0154556.
Nature protocols. 2016-03-01; 11.3: 499-524.
Scientific reports. 2016-02-10; 6.20686.
Cytometry. Part A : the journal of the International Society for Analytical Cytology. 2016-01-01; 89.1: 71-88.
Mapping cell populations in flow cytometry data for cross-sample comparison using the Friedman-Rafsky test statistic as a distance measure
Vaccine. 2015-08-26; 33.36: 4368-82.
Strengthening the influenza vaccine virus selection and development process: Report of the 3rd WHO Informal Consultation for Improving Influenza Vaccine Virus Selection held at WHO headquarters, Geneva, Switzerland, 1-3 April 2014
Immunity. 2015-04-21; 42.4: 591-2.
Scientific data. 2014-10-14; 1.140033.
A comprehensive collection of systems biology data characterizing the host response to viral infection
Nature methods. 2013-03-01; 10.3: 228-38.
Nucleic acids research. 2012-01-01; 40.Database issue: D593-8.
Journal of biomedical informatics. 2011-02-01; 44.1: 3-7.
Viruses. 2010-10-13; 2.10: 2258-2268.
Cytometry. Part B, Clinical cytometry. 2010-01-01; 78 Suppl 1.S69-82.
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
Summit on translational bioinformatics. 2009-03-01; 2009.116-20.
BMC bioinformatics. 2009-02-25; 10.70.
Cytometry. Part A : the journal of the International Society for Analytical Cytology. 2008-10-01; 73.10: 926-30.
Our goal is to improve and utilize machine intelligence for elucidating cancer heterogeneity and disease endotypes for supporting cancer precision medicine.