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Interests:

Artificial intelligence in medicine (AI safety/reliability, grounding, machine learning, knowledge representation and extraction, multi-modal models, and decision making under uncertainty), biomedical data science (data integration, visualization, network analysis), computational biology (pathway analysis, protein structure), and public health informatics (disease surveillance, epidemic models, molecular epidemiology).

Background:

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.

Research:

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.

Current projects:

  • Coronavirus Prevention Network
  • AI Trust and Safety in Biomedicine

Teaching:

  • BIME 530 – Introduction to Biomedical Informatics
  • BIME 534 – Biology and Informatics

Other Roles:

Board Member, Firland Foundation

Other:

High-throughput biology/-Omics, evolutionary processes, bibliometrics, immunology and user interfaces.

Representative publications:

Carroll LN, Au AP, Detwiler LT, Fu TC, Painter IS, Abernethy NF. Visualization and analytics tools for infectious disease epidemiology: a systematic review. Journal of biomedical informatics. 2014 Oct 1;51:287-98.

Cramer, Estee Y., et al. “Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.” Proceedings of the National Academy of Sciences 119.15 (2022): e2113561119.

Goodreau SM, Stansfield SE, Mittler JE, Murphy JT, Abernethy NF, Gottlieb GS, Reid MC, Burke JC, Pollock ED, Herbeck JT. Why does age at HIV infection correlate with set point viral load? An evolutionary hypothesis. Epidemics. 2022 Dec 1;41:100629.

Reid MC, Mittler JE, Murphy JT, Stansfield SE, Goodreau SM, Abernethy N, Herbeck JT. Evolution of HIV virulence in response to disease-modifying vaccines: A modeling study. Vaccine. 2023 Oct 13;41(43):6461-9.

Abernethy NF, McCloskey K, Trahey M, Rinn L, Broder GB, Andrasik M, Laborde R, McGhan D, Spendolini S, Marimuthu S, Kanzmeier A. Rapid Development of a Registry to Accelerate COVID-19 Vaccine Clinical Trials. Research Square. 2024 Jun 10:rs-3.

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.