Epidemiology & Public Health
Institute for Genome Sciences
Health Sciences Facility III, 670 West Baltimore St, Baltimore 21201
Education and Training
- Bachelor of Arts, 1989, Wells College, Major: Biology
- Doctorate of Philosophy, 1997, University of Ottawa, Department of Biology
- IRTA/CRTA Postdoctoral Fellowship, 1996-1999, National Cancer Institute, Frederick Cancer Research and Development Center, Laboratory of Genomic Diversity, Frederick, Maryland
Dr. Lynn M. Schriml is an Associate Professor at the University of Maryland, School of Medicine in the Department of Epidemiology and Public Health and at the Institute of Genome Science (IGS) in Baltimore, Maryland. Dr. Schriml’s current research focuses on developing bioinformatic tools, metadata standards and ontologies to gain a broader understanding of the relationship between infectious pathogens, their genomic sequence and disease.
Dr. Schriml is a member of the Population Science Program within the University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center (UMGCC) Program in Oncology. Population Science researchers collaborate with investigators throughout the University of Maryland System to identify determinants of cancer etiology and survivorship, characterize cancer-related health behaviors, and translate basic discoveries into behavioral cancer prevention and control interventions. Dr. Schriml’s research centers on developing and implementing ontological tools aimed at classifying and unifying cancer nomenclature and term usage.
Dr. Schriml leads a number of ontology and metadata standard development and implementation projects. As PI of the Alfred P. Sloan Foundation funded Built Environment MIxS-BE Metadata project. Dr. Schriml leads efforts to provide tools to foster standard metadata collection and analysis across the Microbiology of the Built Environment program. As PI of the Disease Ontology, Dr. Schriml leads ontology community-based curation, expansion and utilization efforts. The Human Disease Ontology, a broadly adopted standard, is utilized across biomedical databases and resources for knowledge and data sharing through standardized annotation of biomedical data. Dr. Schriml’s group is currently focused on the classification and annotation of rare diseases and cancer, actively engaged with the Model Organism Databases to standardize human diseases associated with animal models.
Dr. Schriml’s work involves extensive collaborative interactions with a diverse community of researchers and development of research projects involving consortiums, government and private sector collaborators. As a project leader, board member (President) and developer in the Genomic Standards Consortium (GSC), Dr. Schriml is a promoter of metadata standards development and integration for genomic projects, including the HMP-DACC and NIAID GSCID projects hosted at the Institute for Genome Sciences, University of Maryland, Baltimore, into large scale genome databases (e.g. NCBI’s BioSample, NIAID BRC’s, JGI’s GOLD database). Dr. Schriml is the primary developer of a suite of OBO Foundry biomedical ontologies including the Disease Ontology, Symptom Ontology, Transmission Method Ontology, Influenza Ontology, Environmental (EnvO) ontology and geographic locations gazetteer (GAZ) vocabulary.
Following Dr. Schriml’s postdoctoral research at the National Cancer Institute - Frederick Cancer Research and Development Center conducting population studies and characterizing mouse ABC-transporters, Dr. Schriml transitioned to bioinformatics. Dr. Schriml development bioinformatics tools for model organism genome projects at the National Center for Biotechnology Information (NCBI) at NIH as a Staff Scientist prior to joining the Institute for Genome Research (TIGR) in 2005 to develop the microbial surveillance Gemina project.
Human Disease Knowledge Representation, Biomedical Ontologies, Genomic Metadata Standards, Epidemiology, Bioinformatics, Data Mining, Big Data, Microbiome, Metagenome
- MetaSUB International Consortium. [Lynn Schriml] The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) International Consortium inaugural meeting report. Microbiome. 2016 Jun 3;4(1):24. doi: 10.1186/s40168-016-0168-z.
- Schriml LM, Mitraka E. (2015) The Disease Ontology: fostering interoperability between biological and clinical human disease-related data. Mamm Genome. 26(9-10):584-589.
- Wu TJ, Schriml LM, Chen QR, Colbert M, Crichton DJ, Finney R, Hu Y, Kibbe WA, Kincaid H, Meerzaman D, Mitraka E, Pan Y, Smith KM, Srivastava S, Ward S, Yan C, Mazumder R. Generating a focused view of disease ontology cancer terms for pan-cancer data integration and analysis. Database (Oxford). 2015;2015:bav032.
- Schriml L. et al. (2013) The 15th Genomic Standards Consortium meeting. Standards in Genomic Sciences. 8:124-164.
Additional Publication Citations
Salomonis N, Dexheimer PJ, Omberg L, Schroll R, Bush S, Huo J, Schriml L, Ho Sui S, Keddache M, Mayhew C, et al. Integrated Genomic Analysis of Diverse Induced Pluripotent Stem Cells from the Progenitor Cell Biology Consortium. Stem Cell Reports. 2016 Jun 9. pii: S2213-6711(16)30061-3.
Kibbe WA, Arze C, Felix V, Mitraka E, Bolton E, Fu G, Mungall CJ, Binder JX, Malone J, Vasant D, Parkinson H, Schriml LM. (2015) Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data. Nucleic Acids Res. 43(Database issue):D1071-1078.
Dawn Field, Peter Sterk, Renzo Kottmann, J. Wim De Smet, Linda Amaral-Zettler, Guy Cochrane, James R. Cole, Neil Davies, Peter Dawyndt, George M. Garrity, Jack A. Gilbert, Frank Oliver Glöckner, Lynette Hirschman, Hans-Peter Klenk, Rob Knight, Nikos Kyrpides, Folker Meyer, Ilene Karsch-Mizrachi, Norman Morrison, Robert Robbins, Inigo San Gil, Susanna Sansone, Lynn Schriml, Tatiana Tatusova, Dave Ussery, Pelin Yilmaz, Owen White, John Wooley, Gregory Caporaso. (2014) Genomic Standards Consortium Projects. Standards in Genomic Sciences. 9:3.
Schriml L. et al. (2013) The 15th Genomic Standards Consortium meeting. Standards in Genomic Sciences. 8:124-164.
EM Glass, Y Dribinsky, P Yilmaz, H Levin, R Van Pelt, D Wendel, A Wilke, J A Eisen, S Huse, A Shipanova, M Sogin, J Stajich, R Knight, F Meyer and LM Schriml. (2013) MIxS-BE: a MIxS extension defining a minimum information standard for sequence data from the built environment. ISME J. 2013 Oct 24.
Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature. 2012. 486:207-714.
Liolios K, Schriml L, Hirschman L, Pagani I, Nosrat B, Sterk P, White O, Rocca-Serra P, Sansone SA, Taylor C, Kyrpides NC, Field D. The Metadata Coverage Index (MCI): A standardized metric for quantifying database metadata richness. Stand Genomic Sci. 2012 Oct 10;7(1):159-65.
Yilmaz P et al. (2011) Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications. Nat Biotechnol. 29:415-420.
Complete List of Published Work in PubMed
Dr. Schriml's research interests include human disease, infectious diseases, ontologies, metadata standards, epidemiology, bioinformatics, data mining, statistics and microbiome.
Dr. Schriml's areas of focus include:
- Biomedical ontologies: development and utilization for exploring BigData and cancer.
- Genome metadata standards development and implementation
- Microbial community diversity and metadata in the built environment
- MetaSub: characterizing transit system metagenomes and microbiomes
- Health Disparities among individuals with Intellectual Disabilities
Awards and Affiliations
University of Maryland School of Medicine, Department of Epidemiologyand Public Health, Medical School Teaching Award, 2015
- President, Genomic Standards Consortium, 2015-2016
Links of Interest
- Alfred P. Sloan Foundation, Microbiology of the Built Environment
- Disease Ontology
- University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center (UMGCC)
- Progenitor Cell Biology Consortium
- Division of Genomic Epidemiology & Clinical Outcomes
- Genomic Standards Consortium (GSC)
- MetaSUB: Transit System Microbiomes