Joseph D Romano, PhD, MPhil, MA

Affiliations: 
2023- Department of Biostatistics, Epidemiology, & Informatics University of Pennsylvania, Philadelphia, PA, United States 
Area:
Translational Bioinformatics, Computational Toxicology
Website:
jdr.bio
Google:
"Joseph D. Romano"

Parents

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Indra N. Sarkar research assistant 2011-2014 University of Vermont (Microtree)
Nicholas Tatonetti grad student 2014-2019 Columbia
Jason H. Moore post-doc 2019- Penn (Computational Biology Tree)
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Publications

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Romano JD, Mei L, Senn J, et al. (2023) Exploring genetic influences on adverse outcome pathways using heuristic simulation and graph data science. Computational Toxicology (Amsterdam, Netherlands). 25
Romano JD, Li H, Napolitano T, et al. (2023) Discovering Venom-Derived Drug Candidates Using Differential Gene Expression. Toxins. 15
Hao Y, Romano JD, Moore JH. (2023) Knowledge graph aids comprehensive explanation of drug and chemical toxicity. Cpt: Pharmacometrics & Systems Pharmacology
Hao Y, Romano JD, Moore JH. (2022) Knowledge-guided deep learning models of drug toxicity improve interpretation. Patterns (New York, N.Y.). 3: 100565
Romano JD, Hao Y, Moore JH, et al. (2022) Automating Predictive Toxicology Using ComptoxAI. Chemical Research in Toxicology
Romano JD, Hao Y, Moore JH. (2022) Improving QSAR Modeling for Predictive Toxicology using Publicly Aggregated Semantic Graph Data and Graph Neural Networks. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 27: 187-198
Manduchi E, Romano JD, Moore JH. (2021) The promise of automated machine learning for the genetic analysis of complex traits. Human Genetics
Romano JD, Le TT, La Cava W, et al. (2021) PMLB v1.0: An open-source dataset collection for benchmarking machine learning methods. Bioinformatics (Oxford, England)
Romano JD, Moore JH. (2020) Ten simple rules for writing a paper about scientific software. Plos Computational Biology. 16: e1008390
Manduchi E, Fu W, Romano JD, et al. (2020) Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses. Bmc Bioinformatics. 21: 430
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