Lindsay Cowell, Ph.D.
Associate Professor

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.

Undergraduate

University of North Carolina A (1992), Education

Graduate School

North Carolina State Universit (1995)

Graduate School

North Carolina State Universit (2000)

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

Featured Publications

Biophysicochemical motifs in T cell receptor sequences distinguish repertoires from tumor-infiltrating lymphocytes and adjacent healthy tissue.

Ostmeyer J, Christley S, Toby IT, Cowell LG Cancer Res. 2019 Jan

Statistical classifiers for diagnosing disease from immune repertoires: a case study using multiple sclerosis.

Ostmeyer J, Christley S, Rounds WH, Toby I, Greenberg BM, Monson NL, Cowell LG BMC Bioinformatics 2017 Sep 18 1 401

Individual heritable differences result in unique cell lymphocyte receptor repertoires of naïve and antigen-experienced cells.

Rubelt F, Bolen CR, McGuire HM, Heiden JA, Gadala-Maria D, Levin M, M Euskirchen G, Mamedov MR, Swan GE, Dekker CL, Cowell LG, Kleinstein SH, Davis MM Nat Commun 2016 7 11112

RAG Represents a Widespread Threat to the Lymphocyte Genome.

Teng G, Maman Y, Resch W, Kim M, Yamane A, Qian J, Kieffer-Kwon KR, Mandal M, Ji Y, Meffre E, Clark MR, Cowell LG, Casellas R, Schatz DG Cell 2015 Aug 162 4 751-65

Haplotype Association Mapping Identifies a Candidate Gene Region in Mice Infected With Staphylococcus aureus.

Johnson NV, Ahn SH, Deshmukh H, Levin MK, Nelson CL, Scott WK, Allen A, Fowler VG, Cowell LG G3 (Bethesda) 2012 Jun 2 6 693-700

Conserved cryptic recombination signals in Vkappa gene segments are cleaved in small pre-B cells.

Lieberman AE, Kuraoka M, Davila M, Kelsoe G, Cowell LG BMC Immunol. 2009 10 37

An improved ontological representation of dendritic cells as a paradigm for all cell types.

Masci AM, Arighi CN, Diehl AD, Lieberman AE, Mungall C, Scheuermann RH, Smith B, Cowell LG BMC Bioinformatics 2009 10 70

Prospective estimation of recombination signal efficiency and identification of functional cryptic signals in the genome by statistical modeling.

Cowell LG, Davila M, Yang K, Kepler TB, Kelsoe G J. Exp. Med. 2003 Jan 197 2 207-20

Identification and utilization of arbitrary correlations in models of recombination signal sequences.

Cowell LG, Davila M, Kepler TB, Kelsoe G Genome Biol. 2002 3 12 RESEARCH0072

The distribution of variation in regulatory gene segments, as present in MHC class II promoters.

Cowell LG, Kepler TB, Janitz M, Lauster R, Mitchison NA Genome Res. 1998 Feb 8 2 124-34