Match tier
Likely match
Presence
Current · Arkansas
Last published
2025
Sources
OpenAlex · ORCID
Refreshed
2026-08-08
D
Dong Wang
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Researcher
Also affiliated: Kanazawa University (2022); Qingdao University (2022); United States Food and Drug Administration (2018–2024); Central South University (2019–2020); Army Medical University (2017–2020); Harbin Medical University (2020–2023); WuXi AppTec (China) (2024); Daping Hospital (2020); People's Hospital of Kaizhou District (2024); Life Science Institute (2022); Affiliated Hospital of Qingdao University (2022); Second Affiliated Hospital of Harbin Medical University (2020–2023); Xiangya Hospital Central South University (2019–2020); First People's Hospital of Chongqing (2024)
Faculty Researcher
9 h-index
23 pubs
254 cited
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Dong Wang's research focuses on the application of genomic and computational methods to understand disease mechanisms and identify predictive biomarkers, particularly in the context of cancer and adverse drug reactions. His work has involved the development and validation of genomic reference samples for assessing cancer detection panels, focusing on low allele frequency variants. Wang has also investigated the prognostic value of circulating tumor DNA in patients with hepatocellular carcinoma and explored extrachromosomal circular DNA-related gene signatures for predicting survival in ovarian cancer patients.
Further research interests include the use of computer simulations for exploring drug-host factor interactions in spontaneous adverse event reporting databases. He has also contributed to understanding the mechanisms of traditional medicine in modulating immune responses for cancer immunotherapy, such as the role of Astragalus polysaccharide and Qizhen decoction in dendritic cell maturation and activation of specific signaling pathways. His collaborations include work with researchers at the National Center for Toxicological Research and the University of Arkansas for Medical Sciences.
Metrics
- h-index: 9
- Publications: 23
- Citations: 254
Selected Publications
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The connection between Bayesian networks and adverse outcome pathway (AOP) networks and how to use it for predicting drug toxicity (2025)
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Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study (2025)
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Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study (2024)
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Identifying Vulnerabilities to NSAID Adverse Events in the U.S. Population: An Analysis of Preexisting Conditions and Sex (2024)
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Predicting oncology drug-induced cardiotoxicity with donor-specific iPSC-CMs—a proof-of-concept study with doxorubicin (2024)
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Assessments of tumor mutational burden estimation by targeted panel sequencing: A comprehensive simulation analysis (2023)
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The impact of misclassification errors on the performance of biomarkers based on next-generation sequencing, a simulation study (2023)
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Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study (2023)
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Identifying Vulnerabilities to NSAID Adverse Events in the US Population: An Analysis of Pre-Existing Conditions and Sex (2023)
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Statistical methods for exploring spontaneous adverse event reporting databases for drug-host factor interactions (2023)
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A targeted simulation‐extrapolation method for evaluating biomarkers based on new technologies in precision medicine (2021)
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Medical Information Mart for Intensive Care: A Foundation for the Fusion of Artificial Intelligence and Real-World Data (2021)
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A verified genomic reference sample for assessing performance of cancer panels detecting small variants of low allele frequency (2021)
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Variational Bayesian inference for association over phylogenetic trees for microorganisms (2020)
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In Silico Prediction of the Point of Departure (POD) with High-Throughput Data (2019)
Collaboration Network
Top Collaborators
Paul Rogers
National Center for Toxicological Research
6 shared publications
In database
- Medical Information Mart for Intensive Care: A Foundation for the Fusion of Artificial Intelligence and Real-World Data
- Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Identifying Vulnerabilities to NSAID Adverse Events in the US Population: An Analysis of Pre-Existing Conditions and Sex
Showing 5 of 6 shared publications
Joshua Xu
National Center for Toxicological Research
4 shared publications
In database
- A targeted simulation‐extrapolation method for evaluating biomarkers based on new technologies in precision medicine
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Assessments of tumor mutational burden estimation by targeted panel sequencing: A comprehensive simulation analysis
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Zhiyuan Lu
National Center for Toxicological Research (US)
3 shared publications
- Statistical methods for exploring spontaneous adverse event reporting databases for drug-host factor interactions
- Identifying Vulnerabilities to NSAID Adverse Events in the US Population: An Analysis of Pre-Existing Conditions and Sex
- Identifying Vulnerabilities to NSAID Adverse Events in the U.S. Population: An Analysis of Preexisting Conditions and Sex
Jessica Reese
University of Oklahoma Health Sciences Center (US)
3 shared publications
- Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Donald J. Johann
Winthrop Rockefeller Foundation
2 shared publications
In database
- A verified genomic reference sample for assessing performance of cancer panels detecting small variants of low allele frequency
- Assessments of tumor mutational burden estimation by targeted panel sequencing: A comprehensive simulation analysis
Sue‐Jane Wang
Center for Drug Evaluation and Research (US)
2 shared publications
- A targeted simulation‐extrapolation method for evaluating biomarkers based on new technologies in precision medicine
- The impact of misclassification errors on the performance of biomarkers based on next-generation sequencing, a simulation study
Samir Lababidi
2 shared publications
- A targeted simulation‐extrapolation method for evaluating biomarkers based on new technologies in precision medicine
- The impact of misclassification errors on the performance of biomarkers based on next-generation sequencing, a simulation study
Ayako Suzuki
Durham VA Medical Center (US)
2 shared publications
- Statistical methods for exploring spontaneous adverse event reporting databases for drug-host factor interactions
- The connection between Bayesian networks and adverse outcome pathway (AOP) networks and how to use it for predicting drug toxicity
Beverly Lyn‐Cook
National Center for Toxicological Research
2 shared publications
In database
- Identifying Vulnerabilities to NSAID Adverse Events in the US Population: An Analysis of Pre-Existing Conditions and Sex
- Identifying Vulnerabilities to NSAID Adverse Events in the U.S. Population: An Analysis of Preexisting Conditions and Sex
Christine Merenda
United States Food and Drug Administration (US)
2 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Richardae Araojo
United States Food and Drug Administration (US)
2 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Christine Lee
United States Food and Drug Administration (US)
2 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Milena Lolic
United States Food and Drug Administration (US)
2 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Ying Zhang
University of Oklahoma Health Sciences Center (US)
2 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Kimberly Malloy
University of Oklahoma Health Sciences Center (US)
2 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
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