Weida Tong Institution-verified
Sourced from institutional research profiles (UAMS TRI or ARA).
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faculty
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Biography and Research Information
OverviewAI-generated summary
Weida Tong leads a research group focused on regulatory science, with a particular emphasis on the application of bioinformatics and emerging technologies. Tong's work investigates the impact of new technologies on regulatory science and explores the use of AI-based language models in drug discovery and development. This research area intersects with public health and the evaluation of scientific reporting guidelines, such as the STORMS checklist for human microbiome research.
Further research interests include the regulatory landscape of nanotechnology and nanoplastics, and the analytical validation of sequencing assays for precision oncology. Tong has a scholarly record with an h-index of 4, encompassing 11 publications and 640 citations. Key collaborators at the National Center for Toxicological Research include Joshua Xu (14 shared publications), Leihong Wu (7 shared publications), William Slikker (4 shared publications), and Binsheng Gong (4 shared publications). Tong is also recognized as an ARA Academy member (ARA Fellow).
Metrics
- h-index: 82
- Publications: 550
- Citations: 29,795
Selected Publications
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AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women (2025)
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Is ChatGPT Ready for Public Use in Organ-Specific Drug Toxicity Research? (2025)
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Bridging organ transcriptomics for advancing multiple organ toxicity assessment with a generative AI approach (2024)
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Physiological liver microtissue 384-well microplate system for preclinical hepatotoxicity assessment of therapeutic small molecule drugs (2024)
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Progress in toxicogenomics to protect human health (2024)
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Text summarization with ChatGPT for drug labeling documents (2024)
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Generation of a drug-induced renal injury list to facilitate the development of new approach methodologies for nephrotoxicity (2024)
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Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project (2023)
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Measurement and Mitigation of Bias in Artificial Intelligence: A Narrative Literature Review for Regulatory Science (2023)
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Quartet DNA reference materials and datasets for comprehensively evaluating germline variant calling performance (2023)
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PLM-ARG: antibiotic resistance gene identification using a pretrained protein language model (2023)
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A generative adversarial network model alternative to animal studies for clinical pathology assessment (2023)
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The Quartet Data Portal: integration of community-wide resources for multiomics quality control (2023)
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Author Correction: Quartet RNA reference materials improve the quality of transcriptomic data through ratio-based profiling (2023)
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DICTrank: The largest reference list of 1318 human drugs ranked by risk of drug-induced cardiotoxicity using FDA labeling (2023)
ARA Academy 2016 ARA Fellow
Dr. Tong's work emphasizes developing bioinformatic tools and methodologies to support FDA research, regulatory science, and personalized medicine. His notable initiatives include the Microarray Quality Control (MAQC) consortium, the Liver Toxicity Knowledge Base (LTKB), in silico drug repositioning for rare disease treatment, and the ArrayTrack suite for pharmacogenomics review.
Policy Impact
Develops bioinformatic tools supporting FDA regulatory science and personalized medicine, anchoring critical federal research infrastructure in Arkansas.
Growth Areas
['Population Health Innovations & Clinical Research']
Collaboration Network
Top Collaborators
- Is ChatGPT Ready for Public Use in Organ-Specific Drug Toxicity Research?
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
- Circulating biomarkers of neurotoxicity: Proteomics approach reveals fluidic endpoints of central nervous system toxicity in a rodent model of neurotoxicity
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