Neil Abernethy, PhD
Models of infectious disease (including TB, HIV, and influenza), molecular epidemiology, network analysis, disease surveillance, data visualization, systems biology, data integration, emerging infections, and global health
B.S. Biochemistry (NCSU); B.S. Applied Mathematics (NCSU); Ph.D. Biomedical Informatics (Stanford University). Dr. Abernethy’s training included molecular evolution, knowledge representation for bioinformatics, network analysis, epidemiology of infectious disease, and interactive data visualization.
Models of infectious disease (including TB, HIV, and influenza), molecular epidemiology, network analysis, disease surveillance, data information, systems biology, data standards and integration, with a focus on infectious diseases and global health.
High-throughput (“Omics”) biology, evolutionary processes, bibliometrics, user interfaces, and artificial intelligence.
- N. F. Abernethy; Automating Social Network Models for Tuberculosis Contact Investigation. Ph.D. Dissertation, Stanford University, September, 2005.
- Jeffries D, Abernethy NF, De Jong BC. Supervised learning for the automated transcription of spacer classification from spoligotype films. Medical Research Council (UK), The Gambia. BMC Informatics 2009 August;10:248.
- Guidry A, Walson J, Abernethy NF. Linking information systems for HIV care and research in Kenya. ACM International Health Informatics 2010.
- B. Walther, S. Hossin, J. Townend, N. F. Abernethy, D. Parker, D. Jeffries, Comparison of Electronic Data Capture (EDC) with the Standard Data Capture Method for Clinical Trial Data ; PLOS One, Sep 23, 2011.
- Abernethy NF, Dereimer K, Small PM: A National Survey of Data Standards in Contact Investigation Forms for Tuberculosis. Proceedings of the American Medical Informatics Association (AMIA) 2011 (in press).
- Deanna Petrochilos, N. F. Abernethy; Assessing Network Characteristics of Cancer-Associated Genes in Metabolic and Signaling Networks; Proceedings of the 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.