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Lynn M. Schriml, PhD

Academic Title:

Associate Professor

Primary Appointment:

Epidemiology & Public Health

Additional Title:

Institute for Genome Sciences

Location:

Health Sciences Facility III, 670 West Baltimore St, Baltimore 21201

Phone (Primary):

(410) 706-6776

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

Biosketch

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.

Research/Clinical Keywords

Human Disease Knowledge Representation, Biomedical Ontologies, Genomic Metadata Standards, Epidemiology, Bioinformatics, Data Mining, Big Data, Microbiome, Metagenome

Highlighted Publications

Additional Publication Citations

Research Interests

Awards and Affiliations

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