Weida Tong

National Center for Toxicological Research — United States

Computer Science · Physical Sciences

82h-index29.8kcitations550works7.22yr avg
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Research Topics

Computational Drug Discovery Methods(140), Gene expression and cancer classification(114), Bioinformatics and Genomic Networks(80), Molecular Biology Techniques and Applications(78), Pharmacogenetics and Drug Metabolism(57)

Publications544 total

Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology
UNC Libraries·2025Open Access
Microphysiological systems as an emerging in vitro approach for the evaluation of drug absorption, distribution, metabolism, and excretion and toxicity
Drug Metabolism and Disposition·2025Open Access
Beyond QSARs: Quantitative Knowledge–Activity Relationships (QKARs) for enhanced drug toxicity prediction
Toxicological Sciences·2025· 1 citedOpen Access
DILIrank 2.0: An updated and expanded database for drug-induced liver injury risk based on FDA labeling and a literature review
Drug Discovery Today·2025Open Access
New approach methodologies (NAMs) for drug-induced liver injury (DILI): Where are we now?
Drug Discovery Today·2025· 4 citedOpen Access
AIVIVE: a novel AI framework for enhanced <i>in vitro</i> to <i>in vivo</i> extrapolation (IVIVE) of toxicogenomics data
Toxicological Sciences·2025· 1 citedOpen Access
AI-Driven Integration of Transcriptomics, Quantum Mechanics, and Physiology for Predicting Drug-Induced Liver Injury in Data-Limited Scenarios
Chemical Research in Toxicology·2025· 1 cited
Federated learning: a privacy-preserving approach to data-centric regulatory cooperation
Frontiers in Drug Safety and Regulation·2025· 1 citedOpen Access
Is regulatory science ready for artificial intelligence?
npj Digital Medicine·2025· 21 citedOpen Access
The connection between Bayesian networks and adverse outcome pathway (AOP) networks and how to use it for predicting drug toxicity
Drug Discovery Today·2025Open Access
DICTrank Is a Reliable Dataset for Cardiotoxicity Prediction Using Machine Learning Methods
Chemical Research in Toxicology·2025· 3 cited
Epidemiological profile and antimicrobial resistance trends of Staphylococcus aureus in Chinese pediatric intensive care units from 2016 to 2022: a multi-center retrospective study
BMC Infectious Diseases·2025· 6 citedOpen Access
AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women
Experimental Biology and Medicine·2025· 27 citedOpen Access
Leveraging FDA Labeling Documents and Large Language Model to Enhance Annotation, Profiling, and Classification of Drug Adverse Events with AskFDALabel
Drug Safety·2025· 9 citedOpen Access
Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study
Experimental Biology and Medicine·2025· 2 citedOpen Access
Bridging organ transcriptomics for advancing multiple organ toxicity assessment with a generative AI approach
npj Digital Medicine·2024· 13 citedOpen Access
Physiological liver microtissue 384-well microplate system for preclinical hepatotoxicity assessment of therapeutic small molecule drugs
Toxicological Sciences·2024· 20 citedOpen Access
Development of a comprehensive open access “molecules with androgenic activity resource (MAAR)” to facilitate risk assessment of chemicals
Experimental Biology and Medicine·2024· 1 citedOpen Access
Progress in toxicogenomics to protect human health
Nature Reviews Genetics·2024· 42 cited
Targeted DNA-seq and RNA-seq of Reference Samples with Short-read and Long-read Sequencing
Scientific Data·2024· 6 citedOpen Access
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Frequent Co-authors

Huixiao Hong(20), Roger Perkins(19), Hong Fang(18), Leming Shi(13), Leming Shi(12), Charles Wang(9), Zhenqiang Su(9), Wendell Jones(8), Daniel M. Sheehan(8), James C. Fuscoe(7), Baitang Ning(7), Christopher E. Mason(7), Wenjun Bao(6), Joshua Xu(6), Andreas Scherer(6), William S. Branham(6), Minjun Chen(6), Lei Guo(5), Stephen Harris(5), Cesare Furlanello(5)