Neil Abernethy, PhD
Data management and analytics (data integration, network analysis, information visualization), computational biology (pathway analysis, protein structure), public health (disease surveillance, epidemic models, molecular epidemiology), and artificial intelligence (machine learning, planning, knowledge representation and decision making under uncertainty).
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 biology/-Omics, evolutionary processes, bibliometrics, immunology and user interfaces.
- 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.