faculty photo

Joseph Daniel Romano, PhD, MPhil, MA

Assistant Professor of Biostatistics and Epidemiology
Department: Biostatistics and Epidemiology
Graduate Group Affiliations

Contact information
403 Blockley Hall
423 Guardian Drive
Philadelphia, PA 19104
Office: 215-573-5571
Education:
B.S. (Molecular Genetics)
University of Vermont, 2014.
M.A. (Biomedical Informatics)
Columbia University, 2016.
MPhil (Biomedical Informatics)
Columbia University, 2018.
PhD (Biomedical Informatics)
Columbia University, 2019.
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Selected Publications

Albi G, Dagliati A, Vavassori C, Pisani L, Bellazzi R, Romano JD, & Colombo GI: Classification of Coronary Artery Disease Severity by Combining Clinical and Gene Expression Variables. 22nd International Conference on Artificial Intelligence in Medicine 2024.

Romano JD, Truong V, Kumar R, Venkatesan M, Graham BE, Hao Y, Matsumoto N, Li X, Wang Z, Ritchie M, Shen L, & Moore JH: The Alzheimer's Knowledge Base: A Knowledge Graph for Alzheimer Disease Research. Journal of Medical Internet Research 26: e46777, 2024.

Li R, Romano JD, Chen Y, & Moore JH: Centralized and Federated Models for the Analysis of Clinical Data. Annual Review of Biomedical Data Science 7, 2024 Notes: (Accepted; in press).

Paris CF, Morales E, & Romano JD: Knowledge-driven artificial intelligence enables mechanistic computational toxicology. NIEHS Environmental Health Sciences Core Centers Annual Meeting October 2023.

Hao Y, Romano JD, & Moore JH: Knowledge Graph Aids Comprehensive Explanation of Drug and Chemical Toxicity. CPT: Pharmacometrics & Systems Pharmacology. Wiley, 12(8): 1072-1079, August 2023.

Romano JD, Li H, Napolitano T, Realubit R, Karan C, Holford M, & Tatonetti NP: Discovering venom-derived drug candidates using differential gene expression. Toxins. MDPI, 15(7): 451, July 2023.

Romano JD, Mei L, Senn J, Moore JH, & Mortensen HM: Exploring genetic influences on adverse outcome pathways using heuristic simulation and graph data science. Computational Toxicology. Elsevier, 25: 100261, February 2023.

Romano JD: Omics Methods in Toxins Research—A Toolkit to Drive the Future of Scientific Inquiry. Toxins 14(11): 761, November 2022.

Manduchi E, Romano JD, & Moore JH: The promise of automated machine learning for the genetic analysis of complex traits. Human Genetics 141(9): 1529–1544, September 2022.

Hao Y, Romano JD, & Moore JH: Knowledge-guided deep learning models of drug toxicity improve interpretation. Patterns 3(9), August 2022.

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Last updated: 04/22/2024
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