Dr. Cowell received a M.S. in Biomathematics with a minor in Mathematics in 1995 from North Carolina State University. In 2000, she received a Ph.D. in Biomathematics with a minor in Immunology, also from North Carolina State University. She spent three years as a postdoctoral fellow in the Department of Immunology at Duke University Medical Center and then became an Assistant Professor in the Department of Biostatistics and Bioinformatics.  She was also on the graduate faculty at Duke for the Computational Biology and Bioinformatics Graduate Program. In September 2010, she joined the Biomedical Informatics Division in the Department of Clinical Sciences at UT Southwestern. Dr. Cowell is broadly interested in understanding the mechanisms of adaptive immunity and their role in infectious diseases, autoimmune diseases, cancer immunology, and vaccine responses. Her methodologic focus has centered on the development of probabilistic models and the use of formal logics for representing and computing with descriptive information. Dr. Cowell is also involved in the educational mission at UT Southwestern. She is a member of the Graduate Program in Immunology. She directs the Introduction to Statistics course for first year graduate students and is involved in training and mentoring graduate students and postdoctoral fellows.


Adaptive Immunity

Research in the Cowell group is directed toward advancing understanding of (1) the molecular mechanisms by which adaptive immune receptor genes are somatically generated and diversified, (2) the role of these mechanisms in disease, and (3) the dynamics of adaptive immune receptor repertoires in the context of various states of human health and disease. In addition to our basic science research, we have pursued clinical applications in the areas of autoimmune disease (e.g., multiple sclerosis), infectious disease (e.g., Staphylococcus aureus, HIV), and cancer immunology (e.g., HPV-related cancers, particularly cervical cancer, ovarian cancer, design of chimeric antigen receptors for cancer therapy).


Computable Representations of Descriptive Biological and Clinical Information 

Dr. Cowell’s research in this area has focused on using formal logics to represent and compute with biological and clinical information in the immunology and infectious diseases domains. She is interested in using logical representations to enhance the analysis of high-throughput biological data and its integration with electronic health record data.


University of North Carolina A (1992), Education
Graduate School
North Carolina State Universit (1995)
Graduate School
North Carolina State Universit (2000)

Research Interest

  • 1. Somatic diversification of antigen receptor encoding genes
  • 2. Antigen receptor repertoire dynamics
  • 3. Biomedical Ontologies and formal logic


Featured Publications LegendFeatured Publications

Expansion of CD27(high) plasmablasts in transverse myelitis patients that utilize VH4 and JH6 genes and undergo extensive somatic hypermutation.
Ligocki AJ, Rounds WH, Cameron EM, Harp CT, Frohman EM, Courtney AM, Vernino S, Cowell LG, Greenberg B, Monson NL Genes Immun. 2013 Apr
CD19-Targeted T Cells Rapidly Induce Molecular Remissions in Adults with Chemotherapy-Refractory Acute Lymphoblastic Leukemia.
Brentjens RJ, Davila ML, Riviere I, Park J, Wang X, Cowell LG, Bartido S, Stefanski J, Taylor C, Olszewska M, Borquez-Ojeda O, Qu J, Wasielewska T, He Q, Bernal Y, Rijo IV, Hedvat C, Kobos R, Curran K, Steinherz P, Jurcic J, Rosenblat T, Maslak P, Frattini M, Sadelain M Sci Transl Med 2013 Mar 5 177 177ra38
Ontology for vector surveillance and management.
Lozano-Fuentes S, Bandyopadhyay A, Cowell LG, Goldfain A, Eisen L J. Med. Entomol. 2013 Jan 50 1 1-14
Towards an ontological representation of resistance: the case of MRSA.
Goldfain A, Smith B, Cowell LG J Biomed Inform 2011 Feb 44 1 35-41