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Institution-verified
Presence
Current · Arkansas
Last published
2026
Sources
Institutional record
Refreshed
2026-10-05
Weida Tong
Sourced from institutional research profiles (UAMS TRI or ARA).
◆ ARA Academy
Division Director
Also affiliated: United States Food and Drug Administration (2020–2021); Center for Devices and Radiological Health (2020); Fudan University (2020); Rhode Island Hospital (2021); Fudan University Shanghai Cancer Center (2020); Lifespan (2021); Sunnybrook Research Institute (2020); Odette Cancer Centre (2020)
4 h-index
7 pubs
705 cited
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Weida Tong leads a research group focused on bioinformatics and regulatory science. His work has investigated the reproducibility and accuracy of gene expression measurements, particularly concerning microarray and RNA sequencing technologies. This includes contributions to the MicroArray Quality Control (MAQC) project and the Sequencing Quality Control Consortium, which assessed inter- and intra-platform reproducibility and the impact of common practices on predictive model development.
Tong's research also encompasses the development and validation of predictive models, including the applicability domain of quantitative structure-activity relationships. He has published on the concordance between different gene expression measurement technologies and the transparency and reproducibility of artificial intelligence. His work has involved collaborations with researchers at the National Center for Toxicological Research, including Huixiao Hong, Joshua Xu, Leihong Wu, and Ting Li.
Metrics
- h-index: 4
- Publications: 7
- Citations: 705
Positions
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Division Director 1996–presentNational Center for Toxicological Research Division of Bioinformatics and Biostatistics Institutional directory
Selected Publications
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Two decades of prescription opioid-related cardiovascular safety signals: a FAERS-based pharmacovigilance study using machine learning (2026)
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Exploring Sex Differences in Cardiac ICU Admission and Length of Stay Using Multiple Correspondence Analysis (2026)
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Is regulatory science ready for artificial intelligence? (2025)
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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)
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
Huixiao Hong
National Center for Toxicological Research
67 shared publications
In database
- A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
- The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance
- A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages
- Comparison of RNA-seq and microarray-based models for clinical endpoint prediction
Showing 5 of 67 shared publications
Hong Fang
National Center for Toxicological Research
54 shared publications
In database
- The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance
- Toward interoperable bioscience data
- Structure−Activity Relationships for a Large Diverse Set of Natural, Synthetic, and Environmental Estrogens
- FDA-approved drug labeling for the study of drug-induced liver injury
- The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies
Showing 5 of 54 shared publications
Roger Perkins
National Center for Toxicological Research (US)
46 shared publications
- A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
- Current Status of Methods for Defining the Applicability Domain of (Quantitative) Structure-Activity Relationships
- Structure−Activity Relationships for a Large Diverse Set of Natural, Synthetic, and Environmental Estrogens
- The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies
Showing 5 of 46 shared publications
Leming Shi
Fudan University (CN)
30 shared publications
- Performance comparison of one-color and two-color platforms within the Microarray Quality Control (MAQC) project
- Structure−Activity Relationships for a Large Diverse Set of Natural, Synthetic, and Environmental Estrogens
- Rat toxicogenomic study reveals analytical consistency across microarray platforms
- A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data
- Mold2, Molecular Descriptors from 2D Structures for Chemoinformatics and Toxicoinformatics
Showing 5 of 30 shared publications
Minjun Chen
United States Food and Drug Administration
23 shared publications
In database
- FDA-approved drug labeling for the study of drug-induced liver injury
- DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans
- High lipophilicity and high daily dose of oral medications are associated with significant risk for drug-induced liver injury
- A Decade of Toxicogenomic Research and Its Contribution to Toxicological Science
- High Daily Dose and Being a Substrate of Cytochrome P450 Enzymes Are Two Important Predictors of Drug-Induced Liver Injury
Showing 5 of 23 shared publications
Zhenqiang Su
National Center for Toxicological Research (US)
22 shared publications
- A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium
- The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance
- A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages
- Comparison of RNA-seq and microarray-based models for clinical endpoint prediction
- Mold2, Molecular Descriptors from 2D Structures for Chemoinformatics and Toxicoinformatics
Showing 5 of 22 shared publications
Ruth Roberts
The Edgbaston Hospital (GB)
21 shared publications
- AI-based language models powering drug discovery and development
- Drug-induced liver injury severity and toxicity (DILIst): binary classification of 1279 drugs by human hepatotoxicity
- Toxicogenomics: A 2020 Vision
- Toward Clinical Implementation of Next-Generation Sequencing-Based Genetic Testing in Rare Diseases: Where Are We?
- Lessons Learned from Two Decades of Anticancer Drugs
Showing 5 of 21 shared publications
Baitang Ning
National Center for Toxicological Research
19 shared publications
In database
- A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
- A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages
- An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era
- Next-generation sequencing and its applications in molecular diagnostics
Showing 5 of 19 shared publications
Joshua Xu
National Center for Toxicological Research
19 shared publications
In database
- The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance
- An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era
- Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles
- Correcting batch effects in large-scale multiomics studies using a reference-material-based ratio method
- Assessing batch effects of genotype calling algorithm BRLMM for the Affymetrix GeneChip Human Mapping 500 K array set using 270 HapMap samples
Showing 5 of 19 shared publications
Weigong Ge
National Center for Toxicological Research
19 shared publications
In database
- A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
- Persistent Organic Pollutants in Food: Contamination Sources, Health Effects and Detection Methods
- Mold2, Molecular Descriptors from 2D Structures for Chemoinformatics and Toxicoinformatics
- An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era
Showing 5 of 19 shared publications
Leming Shi
Fudan University (CN)
18 shared publications
- The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements
- The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
- The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies
- QSAR Models Using a Large Diverse Set of Estrogens
Showing 5 of 18 shared publications
Lei Guo
National Center for Toxicological Research
16 shared publications
In database
- A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium
- A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages
- Rat toxicogenomic study reveals analytical consistency across microarray platforms
- The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies
- Cross-platform comparability of microarray technology: Intra-platform consistency and appropriate data analysis procedures are essential
Showing 5 of 16 shared publications
James C. Fuscoe
National Center for Toxicological Research
16 shared publications
In database
- A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
- Performance comparison of one-color and two-color platforms within the Microarray Quality Control (MAQC) project
- A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages
- The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies
Showing 5 of 16 shared publications
Jürgen Borlak
Medizinische Hochschule Hannover (DE)
14 shared publications
- High lipophilicity and high daily dose of oral medications are associated with significant risk for drug-induced liver injury
- A Decade of Toxicogenomic Research and Its Contribution to Toxicological Science
- Toward Predictive Models for Drug-Induced Liver Injury in Humans: Are we There Yet?
- Quantitative Structure-Activity Relationship Models for Predicting Drug-Induced Liver Injury Based on FDA-Approved Drug Labeling Annotation and Using a Large Collection of Drugs
- A Model to predict severity of drug‐induced liver injury in humans
Showing 5 of 14 shared publications
Shraddha Thakkar
Center for Drug Evaluation and Research (US)
13 shared publications
- DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans
- Regulatory landscape of dietary supplements and herbal medicines from a global perspective
- Drug-induced liver injury severity and toxicity (DILIst): binary classification of 1279 drugs by human hepatotoxicity
- Development of Decision Forest Models for Prediction of Drug-Induced Liver Injury in Humans Using A Large Set of FDA-approved Drugs
- Study of serious adverse drug reactions using FDA-approved drug labeling and MedDRA
Showing 5 of 13 shared publications
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