معرفی
Lindsay Cowell is a faculty member at UT Southwestern Medical Center, currently affiliated with the Peter O'Donnell Jr. School of Public Health in the Department of Population and Data Sciences. She holds a secondary appointment in the Department of Immunology within the School of Biomedical Sciences and is actively involved in the Computational Biology and Bioinformatics, Immunology, and Cancer Biology graduate programs.
Her educational background includes a Ph.D. and M.S. in Biomathematics from North Carolina State University, with minors in Mathematics and Immunology. She completed postdoctoral training in the Department of Immunology at Duke University Medical Center before joining Duke’s faculty in Biostatistics and Bioinformatics. In 2010, she transitioned to UT Southwestern, where she has remained through departmental reorganizations.
Dr. Cowell's research focuses on the mechanisms of adaptive immunity, particularly the somatic generation and diversification of immune receptor genes, repertoire dynamics, and their implications in health and disease. Her work spans autoimmune disorders (e.g., multiple sclerosis), infectious diseases (e.g., Staphylococcus aureus, HIV), and cancer immunology (e.g., cervical, ovarian, kidney cancers). She employs bioinformatics, statistical modeling, and machine learning to analyze high-dimensional immune repertoire data, aiming to develop computable representations for clinical diagnostics and precision medicine.
Her recent publications reflect a strong trend in immune repertoire profiling, computational tool development (e.g., VDJServer, TCRMatch), ontology integration, and large-scale data analysis for public health questions, including post-COVID outcomes and vaccine safety. These works span disciplines from molecular immunology to population health, demonstrating a systems-level approach to biomedical informatics.
- Haplotype association mapping in infection models
- Development of ontologies for immunology and infectious diseases
- Statistical modeling of recombination signals
- Machine learning for immune repertoire classification
- Cloud-based platforms for immune receptor analysis
- Translational applications in cancer and autoimmune disease
Dr. Cowell has been instrumental in advancing data sharing standards through the AIRR Community, promoting reproducibility and reuse of immune repertoire data. She has contributed to major collaborative efforts in developing APIs, data commons, and analysis pipelines. Her work is supported by interdisciplinary collaborations across immunology, bioinformatics, and clinical research.
She is affiliated with key research initiatives including VDJServer and the AIRR Community, which foster federated data analysis and tool interoperability. Her lab integrates high-performance computing with biological insight to model immune responses at scale.
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