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Listed
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-10-05
H
Research Areas
Biomedical Subjects
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Biography and Research Information
OverviewAI-generated summary
Huixiao Hong's research centers on the application of machine learning and multi-omics data integration for toxicity prediction and cancer mutation detection. Hong has developed quantitative structure-activity relationship (QSAR) models to predict binding affinity, specifically focusing on PPARγ, using large datasets and machine learning algorithms. Their work also addresses the correction of batch effects in large-scale multiomics studies through reference-material-based ratio methods.
Further research includes developing machine learning models for predicting the cytotoxicity of nanomaterials and advancing best practices for cancer mutation detection using whole-genome and whole-exome sequencing. Hong is also involved in establishing community reference samples and data for benchmarking mutation detection methods. Their recent publications highlight a focus on epigenomics quality control and the integration of multi-omics data using quantitative profiling with reference materials.
Hong's scholarship metrics include an h-index of 73, 380 total publications, and over 20,000 citations, designating them as a highly cited researcher. Key collaborators at the National Center for Toxicological Research include Wenjing Guo, Tucker A. Patterson, Weida Tong, and Fan Dong, with whom Hong has co-authored numerous publications.
Metrics
- h-index: 73
- Publications: 380
- Citations: 20,717
Positions
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SBRBPAS Expert 2000–presentNational Center for Toxicological Research Bioinformatics ORCID
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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Integrating Molecular Dynamics, Molecular Docking, and Machine Learning for Predicting SARS-CoV-2 Papain-like Protease Binders (2025)
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Multimodal feature fusion machine learning for predicting chronic injury induced by engineered nanomaterials (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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Analysis of Structures of SARS-CoV-2 Papain-like Protease Bound with Ligands Unveils Structural Features for Inhibiting the Enzyme (2025)
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Unlocking the potential of AI: Machine learning and deep learning models for predicting carcinogenicity of chemicals (2024)
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Perspectives on Advancing Multimodal Learning in Environmental Science and Engineering Studies (2024)
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Determining high priority disinfection byproducts based on experimental aquatic toxicity data and predictive models: Virtual screening and in vivo study (2024)
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Machine learning and deep learning approaches for enhanced prediction of hERG blockade: a comprehensive QSAR modeling study (2024)
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BERT-based language model for accurate drug adverse event extraction from social media: implementation, evaluation, and contributions to pharmacovigilance practices (2024)
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Computational Nanotoxicology Models for Environmental Risk Assessment of Engineered Nanomaterials (2024)
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Fingerprinting Interactions between Proteins and Ligands for Facilitating Machine Learning in Drug Discovery (2024)
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Machine learning and deep learning for brain tumor MRI image segmentation (2023)
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Review of machine learning and deep learning models for toxicity prediction (2023)
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Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project (2023)
Collaboration Network
Top Collaborators
Weida Tong
National Center for Toxicological Research
83 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
- Study of 202 Natural, Synthetic, and Environmental Chemicals for Binding to the Androgen Receptor
- A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data
Showing 5 of 83 shared publications
Roger Perkins
National Center for Toxicological Research (US)
35 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
- Study of 202 Natural, Synthetic, and Environmental Chemicals for Binding to the Androgen Receptor
- Mold2, Molecular Descriptors from 2D Structures for Chemoinformatics and Toxicoinformatics
- Decision Forest: Combining the Predictions of Multiple Independent Decision Tree Models
Showing 5 of 35 shared publications
Weigong Ge
National Center for Toxicological Research
26 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 26 shared publications
Hong Fang
National Center for Toxicological Research
25 shared publications
In database
- The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance
- Study of 202 Natural, Synthetic, and Environmental Chemicals for Binding to the Androgen Receptor
- 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
- Decision Forest: Combining the Predictions of Multiple Independent Decision Tree Models
Showing 5 of 25 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
Leming Shi
Fudan University (CN)
22 shared publications
- 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
- ArrayTrack--supporting toxicogenomic research at the U.S. Food and Drug Administration National Center for Toxicological Research.
- An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era
- Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures
Showing 5 of 22 shared publications
Sugunadevi Sakkiah
National Center for Toxicological Research
22 shared publications
In database
- Persistent Organic Pollutants in Food: Contamination Sources, Health Effects and Detection Methods
- Molecular dynamics simulations and applications in computational toxicology and nanotoxicology
- Machine Learning Models for Predicting Cytotoxicity of Nanomaterials
- Similarities and differences between variants called with human reference genome HG19 or HG38
- Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A
Showing 5 of 22 shared publications
Jie Liu
National Center for Toxicological Research
20 shared publications
In database
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
- Predicting Hepatotoxicity Using ToxCastin VitroBioactivity and Chemical Structure
- Review of machine learning and deep learning models for toxicity prediction
- Machine Learning Models for Predicting Cytotoxicity of Nanomaterials
- Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies
Showing 5 of 20 shared publications
Wenjing Guo
National Center for Toxicological Research
20 shared publications
In database
- Persistent Organic Pollutants in Food: Contamination Sources, Health Effects and Detection Methods
- Review of machine learning and deep learning models for toxicity prediction
- Machine Learning Models for Predicting Cytotoxicity of Nanomaterials
- Similarities and differences between variants called with human reference genome HG19 or HG38
- Nanomaterial Databases: Data Sources for Promoting Design and Risk Assessment of Nanomaterials
Showing 5 of 20 shared publications
Baitang Ning
National Center for Toxicological Research
17 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 17 shared publications
Tucker A. Patterson
National Center for Toxicological Research
17 shared publications
In database
- Review of machine learning and deep learning models for toxicity prediction
- Machine Learning Models for Predicting Cytotoxicity of Nanomaterials
- Nanomaterial Databases: Data Sources for Promoting Design and Risk Assessment of Nanomaterials
- Elucidating Interactions Between SARS-CoV-2 Trimeric Spike Protein and ACE2 Using Homology Modeling and Molecular Dynamics Simulations
- Machine learning and deep learning for brain tumor MRI image segmentation
Showing 5 of 17 shared publications
Hui Wen Ng
National Center for Toxicological Research (US)
16 shared publications
- CERAPP: Collaborative Estrogen Receptor Activity Prediction Project
- Human Sex Hormone-Binding Globulin Binding Affinities of 125 Structurally Diverse Chemicals and Comparison with Their Binding to Androgen Receptor, Estrogen Receptor, and α-Fetoprotein
- Competitive molecular docking approach for predicting estrogen receptor subtype α agonists and antagonists
- Estrogenic Activity Data Extraction and in Silico Prediction Show the Endocrine Disruption Potential of Bisphenol A Replacement Compounds
- Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A
Showing 5 of 16 shared publications
Leming Shi
Fudan University (CN)
15 shared publications
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
- Next-generation sequencing and its applications in molecular diagnostics
- Correcting batch effects in large-scale multiomics studies using a reference-material-based ratio method
- Comparing Next-Generation Sequencing and Microarray Technologies in a Toxicological Study of the Effects of Aristolochic Acid on Rat Kidneys
- Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies
Showing 5 of 15 shared publications
Ying Yu
Fudan University (CN)
12 shared publications
- 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
- Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing
- Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials
- Correcting batch effects in large-scale multiomics studies using a reference-material-based ratio method
Showing 5 of 12 shared publications
Wenming Xiao
National Center for Toxicological Research (US)
12 shared publications
- Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing
- Similarities and differences between variants called with human reference genome HG19 or HG38
- Multiple microRNAs function as self-protective modules in acetaminophen-induced hepatotoxicity in humans
- Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample
- Quartet DNA reference materials and datasets for comprehensively evaluating germline variant calling performance
Showing 5 of 12 shared publications
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