H. Fang

发表

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Hanlee P. Ji, G. M. Fischer, Stephen C. Harris, 2006, Nature biotechnology.

Comparing next-generation sequencing and microarray technologies in a toxicological study of the effects of aristolochic acid on rat kidneys.

Leming Shi, W. Tong, H. Fang, 2011, Chemical research in toxicology.

A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control consortium

David P. Kreil, Todd M. Smith, Thomas M. Blomquist, 2014, Nature Biotechnology.

atBioNet– an integrated network analysis tool for genomics and biomarker discovery

Stephen C. Harris, M. Zhang, W. Tong, 2012, BMC Genomics.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

Kevin C. Dorff, Aaron M. Smalter, Stephen C. Harris, 2010, Nature Biotechnology.

QSAR Models Using a Large Diverse Set of Estrogens.

W. Tong, H. Fang, R. Perkins, 2001 .

Comparative molecular field analysis (CoMFA) model using a large diverse set of natural, synthetic and environmental chemicals for binding to the androgen receptor

H. Fang, H. Hong, R. Perkins, 2003, SAR and QSAR in environmental research.

Toward interoperable bioscience data

Anne E. Trefethen, Catherine A. Shang, Gully A. Burns, 2012, Nature Genetics.

Potential Reuse of Oncology Drugs in the Treatment of Rare Diseases.

W. Tong, H. Fang, W. Slikker, 2016, Trends in pharmacological sciences.

The estrogen receptor relative binding affinities of 188 natural and xenochemicals: structural diversity of ligands.

H Fang, W S Branham, D M Sheehan, 2000, Toxicological sciences : an official journal of the Society of Toxicology.

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.

Weida Tong, Huixiao Hong, Hong Fang, 2015, Toxicological sciences : an official journal of the Society of Toxicology.

Next-Generation Sequencing: A Revolutionary Tool for Toxicogenomics

Leming Shi, W. Tong, H. Fang, 2011 .

ArrayTrack - Supporting Toxicogenomic Research at the FDA?s National Center for Toxicological Research (NCTR)

Stephen C. Harris, Leming Shi, W. Tong, 2003 .

Consistency of predictive signature genes and classifiers generated using different microarray platforms

Tieliu Shi, T. Nikolskaya, Y. Nikolsky, 2010, The Pharmacogenomics Journal.

Performance comparison of one-color and two-color platforms within the Microarray Quality Control (MAQC) project

P. Collins, P. Hurban, Leming Shi, 2006, Nature Biotechnology.

ArrayTrack: a free FDA bioinformatics tool to support emerging biomedical research -- an update

W. Tong, H. Fang, R. Kelly, 2010, Human Genomics.

Next-generation sequencing and its applications in molecular diagnostics

Leming Shi, W. Tong, H. Fang, 2011, Expert review of molecular diagnostics.

Quantitative structure‐activity relationship methods: Perspectives on drug discovery and toxicology

W. Tong, H. Fang, R. Perkins, 2003, Environmental toxicology and chemistry.

Exploring the FDA Adverse Event Reporting System to Generate Hypotheses for Monitoring of Disease Characteristics

H. Fang, Z. Su, Z. Liu, 2014, Clinical pharmacology and therapeutics.

Molecular regulation of miRNAs and potential biomarkers in the progression of hepatic steatosis to NASH.

W. Tong, H. Fang, H. Hong, 2015, Biomarkers in medicine.

NETBAGs: a network-based clustering approach with gene signatures for cancer subtyping analysis.

W. Xiao, W. Tong, H. Fang, 2015, Biomarkers in medicine.

Comparative analysis of predictive models for nongenotoxic hepatocarcinogenicity using both toxicogenomics and quantitative structure-activity relationships.

Weida Tong, Hong Fang, Reagan Kelly, 2011, Chemical research in toxicology.

An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

Weida Tong, Huixiao Hong, Leming Shi, 2014, Genome Biology.

Multiclass Decision Forest--a novel pattern recognition method for multiclass classification in microarray data analysis.

Weida Tong, Qian Xie, Huixiao Hong, 2004, DNA and cell biology.

FDA-approved drug labeling for the study of drug-induced liver injury.

Weida Tong, Hong Fang, Zhichao Liu, 2011, Drug discovery today.

Molecular Biomarkers for Personalized Medicine

Leming Shi, W. Tong, H. Fang, 2014 .

Genomic indicators in the blood predict drug-induced liver injury

H Fang, T. Nikolskaya, Y. Nikolsky, 2010, The Pharmacogenomics Journal.

Prediction of estrogen receptor binding for 58,000 chemicals using an integrated system of a tree-based model with structural alerts.

Weida Tong, Qian Xie, Huixiao Hong, 2001, Environmental health perspectives.

Quantitative comparisons of in vitro assays for estrogenic activities.

H Fang, D M Sheehan, H. Fang, 2000, Environmental health perspectives.

Does Applicability Domain Exist in Microarray-Based Genomic Research?

Weida Tong, Hong Fang, Leihong Wu, 2010, PloS one.

The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

Weida Tong, Qian Xie, Huixiao Hong, 2007 .

Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies

Christophe G. Lambert, Weida Tong, Huixiao Hong, 2012, PloS one.

Evaluating variations of genotype calling: a potential source of spurious associations in genome-wide association studies

Weida Tong, Huixiao Hong, Leming Shi, 2010, Journal of Genetics.

Pitfall of genome-wide association studies: Sources of inconsistency in genotypes and their effects

Weida Tong, Huixiao Hong, Leming Shi, 2012 .

Using Decision Forest to Classify Prostate Cancer Samples on the Basis of SELDI-TOF MS Data: Assessing Chance Correlation and Prediction Confidence

Weida Tong, Qian Xie, Huixiao Hong, 2004, Environmental health perspectives.

Receptor-Mediated Toxicity: QSARs for Estrogen Receptor Binding and Priority Setting of Potential Estrogenic Endocrine Disruptors

Weida Tong, Qian Xie, Huixiao Hong, 2004 .

Self-self hybridization as an alternative experiment design to dye swap for two-color microarrays.

Leming Shi, W. Tong, Y. Dragan, 2007, Omics : a journal of integrative biology.

Toward predictive models for drug-induced liver injury in humans: are we there yet?

Weida Tong, Huixiao Hong, Hong Fang, 2014, Biomarkers in medicine.

Drug-Induced Liver Injury (DILI) Classification and Its Application on Human DILI Risk Prediction

W. Tong, H. Fang, H. Hong, 2018 .

Interpretation of Toxicogenomics Data

W. Tong, H. Fang, R. Perkins, 2010 .

FDA drug labeling: rich resources to facilitate precision medicine, drug safety, and regulatory science.

Weida Tong, Hong Fang, Zhichao Liu, 2016, Drug discovery today.

SNPTrackTM : an integrated bioinformatics system for genetic association studies

Weida Tong, Huixiao Hong, Hong Fang, 2012, Human Genomics.

Cross-Platform Comparison of Microarray-Based Multiple-Class Prediction

W. Tong, H. Fang, Xiaohui Fan, 2011, PloS one.

Correlation analysis of external RNA controls reveals its utility for assessment of microarray assay.

Leming Shi, W. Tong, H. Fang, 2009, Analytical biochemistry.

Identification of New SRF Binding Sites in Genes Modulated by SRF Over-Expression in Mouse Hearts

W. Tong, H. Fang, Y. Zhong, 2011, Gene regulation and systems biology.

Unravelling Sex Differences in Drug‐Induced Liver Injury

W. Tong, H. Fang, Minjun Chen, 2011 .

Threshold analysis of selected dose‐resmnse data for endocrine active chemicals

D. Gaylor, H. Fang, R. Blair, 2001 .

Threshold analysis of selected dose‐response data for endocrine active chemicals Note

D. Gaylor, H. Fang, R. Blair, 2001, APMIS : acta pathologica, microbiologica, et immunologica Scandinavica.

Investigating drug repositioning opportunities in FDA drug labels through topic modeling

Xiaowei Xu, Weida Tong, Hong Fang, 2012, BMC Bioinformatics.

Investigating drug repositioning opportunities in FDA drug labels through topic modeling

W. Tong, H. Fang, R. Kelly, 2012, BMC Bioinformatics.

Structure-activity relationships for a large diverse set of natural, synthetic, and environmental estrogens.

Q Xie, H Fang, D M Sheehan, 2001, Chemical research in toxicology.

QSAR models in receptor-mediated effects: the nuclear receptor superfamily

William J. Welsh, Weida Tong, Hong Fang, 2003 .

Integrating Drug's Mode of Action into Quantitative Structure-Activity Relationships for Improved Prediction of Drug-Induced Liver Injury

Minjun Chen, Leihong Wu, Zhichao Liu, 2017, J. Chem. Inf. Model..

Study of 202 natural, synthetic, and environmental chemicals for binding to the androgen receptor.

Weida Tong, Qian Xie, Huixiao Hong, 2003, Chemical research in toxicology.

Reproducible and reliable microarray results through quality control: good laboratory proficiency and appropriate data analysis practices are essential.

Weida Tong, Leming Shi, Hong Fang, 2008, Current opinion in biotechnology.

An integrated "4-phase" approach for setting endocrine disruption screening priorities--phase I and II predictions of estrogen receptor binding affinity

H Hong, W Tong, Q Xie, 2002, SAR and QSAR in environmental research.

QSAR Models Using a Large Diverse Set of Estrogens

Weida Tong, Leming Shi, Hong Fang, 2001, J. Chem. Inf. Comput. Sci..

Classification of cDNA array genes that have a highly significant discriminative power due to their unique distribution in four brain regions.

Weida Tong, Leming Shi, Hong Fang, 2004, DNA and cell biology.

Toxicogenomics and Cell-Based Assays for Toxicology

W. Tong, H. Fang, D. Mendrick, 2009 .

A proposed OB-fold with a protein-interaction surface in Candida albicans telomerase protein Est3

W. Tong, H. Fang, D. Mendrick, 2009 .

Impact of RNA-seq data analysis algorithms on gene expression estimation and downstream prediction

May D. Wang, Weida Tong, Leming Shi, 2020, Scientific Reports.

Omics Biomarkers in Risk Assessment: A Bioinformatics Perspective

Weida Tong, Huixiao Hong, Reagan Kelly, 2013 .

QA/QC: challenges and pitfalls facing the microarray community and regulatory agencies

Weida Tong, Leming Shi, Hong Fang, 2004, Expert review of molecular diagnostics.

k-Nearest neighbor models for microarray gene expression analysis and clinical outcome prediction

Todd H. Stokes, W Tong, R M Parry, 2010, The Pharmacogenomics Journal.

A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data

Tieliu Shi, Leming Shi, W. Tong, 2010, The Pharmacogenomics Journal.

Assessing sources of inconsistencies in genotypes and their effects on genome-wide association studies with HapMap samples

F. Goodsaid, H. Fang, W. Ge, 2010, The Pharmacogenomics Journal.

An integrated bioinformatics infrastructure essential for advancing pharmacogenomics and personalized medicine in the context of the FDA's Critical Path Initiative.

Weida Tong, Leming Shi, Hong Fang, 2007, Drug discovery today. Technologies.

Evaluation of external RNA controls for the assessment of microarray performance

Weida Tong, Huixiao Hong, Leming Shi, 2006, Nature Biotechnology.

An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

Wenwei Zhang, Yanyan Zhang, Leming Shi, 2014, Genome Biology.

In silico drug repositioning: what we need to know.

Weida Tong, Hong Fang, Zhichao Liu, 2013, Drug discovery today.

An FDA bioinformatics tool for microbial genomics research on molecular characterization of bacterial foodborne pathogens using microarrays

James J. Chen, Weida Tong, Hong Fang, 2010, BMC Bioinformatics.

Constructing a robust protein-protein interaction network by integrating multiple public databases

Xiaowei Xu, Weida Tong, Hong Fang, 2011, BMC Bioinformatics.

A testing strategy to predict risk for drug-induced liver injury in humans using high-content screen assays and the ‘rule-of-two’ model

Weida Tong, Leming Shi, Hong Fang, 2014, Archives of Toxicology.

Cross-platform comparability of microarray technology: Intra-platform consistency and appropriate data analysis procedures are essential

Tao Han, James J. Chen, Weida Tong, 2005, BMC Bioinformatics.

Microarray scanner calibration curves: characteristics and implications

Tao Han, James J. Chen, Weida Tong, 2005, BMC Bioinformatics.

A systems approach for analysis of high content screening assay data with topic modeling

Yuping Wang, Xiaowei Xu, Weida Tong, 2013, BMC Bioinformatics.

Structure‐activity relationship approaches and applications

Weida Tong, Leming Shi, Hong Fang, 2003, Environmental toxicology and chemistry.

Mining FDA drug labels using an unsupervised learning technique - topic modeling

Xiaowei Xu, Weida Tong, Hong Fang, 2011, BMC Bioinformatics.

Very Important Pool (VIP) genes – an application for microarray-based molecular signatures

Weida Tong, Huixiao Hong, Leming Shi, 2008, BMC Bioinformatics.

The Liver Toxicity Knowledge Base (LKTB) and drug-induced liver injury (DILI) classification for assessment of human liver injury

Weida Tong, Hong Fang, Zhichao Liu, 2018, Expert review of gastroenterology & hepatology.

The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

Catalin C. Barbacioru, Leming Shi, Hong Fang, 2008, BMC Bioinformatics.

Multiple microRNAs function as self-protective modules in acetaminophen-induced hepatotoxicity in humans

W. Xiao, Tieliu Shi, Leming Shi, 2018, Archives of Toxicology.

Shifting from Population-wide to Personalized Cancer Prognosis with Microarrays

Leming Shi, W. Tong, H. Fang, 2012, PloS one.

Translating Clinical Findings into Knowledge in Drug Safety Evaluation - Drug Induced Liver Injury Prediction System (DILIps)

Weida Tong, Hong Fang, Reagan Kelly, 2011, PLoS Comput. Biol..

Study of serious adverse drug reactions using FDA-approved drug labeling and MedDRA

Weida Tong, Hong Fang, Leihong Wu, 2019, BMC Bioinformatics.

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.

Weida Tong, Huixiao Hong, Hong Fang, 2013, Toxicological sciences : an official journal of the Society of Toxicology.

ArrayTrack--supporting toxicogenomic research at the U.S. Food and Drug Administration National Center for Toxicological Research.

Weida Tong, Qian Xie, Huixiao Hong, 2003, Environmental health perspectives.

An in silico ensemble method for lead discovery: decision forest

H Hong, W Tong, Q Xie, 2005, SAR and QSAR in environmental research.

Gene expression profile exploration of a large dataset on chronic fatigue syndrome.

Weida Tong, Qian Xie, Hong Fang, 2006, Pharmacogenomics.

ebTrack: an environmental bioinformatics system built upon ArrayTrack™

Weida Tong, Hong Fang, Panos G Georgopoulos, 2009, BMC proceedings.

Mold2, Molecular Descriptors from 2D Structures for Chemoinformatics and Toxicoinformatics

Weida Tong, Huixiao Hong, Leming Shi, 2008, J. Chem. Inf. Model..

Homology modeling, molecular docking, and molecular dynamics simulations elucidated α-fetoprotein binding modes

Weida Tong, Huixiao Hong, Hong Fang, 2013, BMC Bioinformatics.

Assessing batch effects of genotype calling algorithm BRLMM for the Affymetrix GeneChip Human Mapping 500 K array set using 270 HapMap samples

Tao Han, James J. Chen, Weida Tong, 2008, BMC Bioinformatics.

Development of public toxicogenomics software for microarray data management and analysis.

Weida Tong, Qian Xie, Huixiao Hong, 2004, Mutation research.

Gene Expression Profiles Distinguish the Carcinogenic Effects of Aristolochic Acid in Target (Kidney) and Non-target (Liver) Tissues in Rats

Tao Chen, Lu Zhang, Leming Shi, 2006, BMC Bioinformatics.

Artificial intelligence and real-world data for drug and food safety - A regulatory science perspective.

Kern Rei Chng, W. Tong, H. Fang, 2023, Regulatory toxicology and pharmacology : RTP.

The Liver Toxicity Knowledge Base: A Systems Approach to a Complex End Point

H Fang, H. Fang, R. Kelly, 2013, Clinical pharmacology and therapeutics.

Phytoestrogens and mycoestrogens bind to the rat uterine estrogen receptor.

Weida Tong, Leming Shi, Hong Fang, 2002, The Journal of nutrition.

Supplementary Tables 1–6

Tieliu Shi, T. Nikolskaya, Y. Nikolsky, 2010 .

The Accurate Prediction of Protein Family from Amino Acid Sequence by Measuring Features of Sequence Fragments

Weida Tong, Huixiao Hong, Leming Shi, 2009, J. Comput. Biol..

Mold2 Molecular Descriptors for QSAR

Svetoslav H. Slavov, Weida Tong, Huixiao Hong, 2012 .

FDALabel for drug repurposing studies and beyond

Stephen C. Harris, W. Tong, H. Fang, 2020, Nature Biotechnology.

Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling

Weida Tong, Huixiao Hong, Leming Shi, 2005, BMC Bioinformatics.

Approaches and Practical Considerations for the Analysis of Toxicogenomics Data

Weida Tong, Huixiao Hong, Leming Shi, 2011 .

Homology modeling, molecular docking, and molecular dynamics simulations elucidated α-fetoprotein binding modes

W. Tong, H. Fang, H. Hong, 2013, BMC Bioinformatics.

EADB: an estrogenic activity database for assessing potential endocrine activity.

Weida Tong, Huixiao Hong, Hong Fang, 2013, Toxicological sciences : an official journal of the Society of Toxicology.

The EDKB: an established knowledge base for endocrine disrupting chemicals

Lei Xu, Weida Tong, Huixiao Hong, 2010, BMC Bioinformatics.

Decision Forest: Combining the Predictions of Multiple Independent Decision Tree Models

Weida Tong, Huixiao Hong, Hong Fang, 2003, J. Chem. Inf. Comput. Sci..

Regulatory application of SAR/QSAR for priority setting of endocrine disruptors: A perspective

Weida Tong, Qian Xie, Huixiao Hong, 2003 .

Development of Quantitative Structure-Activity Relationships ( QSARs ) and Their Use for Priority Setting in the Testing Strategy of Endocrine Disruptors

Weida Tong, Qian Xie, Huixiao Hong, 2002 .

GOFFA: Gene Ontology For Functional Analysis – A FDA Gene Ontology Tool for Analysis of Genomic and Proteomic Data

Tao Chen, Weida Tong, Hong Fang, 2006, BMC Bioinformatics.

Meta-analysis of microarray data using a pathway-based approach identifies a 37-gene expression signature for systemic lupus erythematosus in human peripheral blood mononuclear cells

Weida Tong, Hong Fang, Shashi Amur, 2011, BMC medicine.

Differential gene expression in mouse primary hepatocytes exposed to the peroxisome proliferator-activated receptor alpha agonists

Leming Shi, W. Tong, Y. Dragan, 2006, BMC Bioinform..

ArrayTrack: an FDA and public genomic tool.

Weida Tong, Leming Shi, Hong Fang, 2009, Methods in molecular biology.

A testing strategy to predict risk for drug-induced liver injury in humans using high-content screen assays and the ‘rule-of-two’ model

Leming Shi, W. Tong, H. Fang, 2014, Archives of Toxicology.

Study of pharmacogenomic information in FDA-approved drug labeling to facilitate application of precision medicine.

Stephen C. Harris, W. Tong, H. Fang, 2020, Drug discovery today.

DNA Microarrays Are Predictive of Cancer Prognosis: A Re-evaluation

Weida Tong, Leming Shi, Yiyu Cheng, 2010, Clinical Cancer Research.

Decision forest for classification of gene expression data

Hong Fang, Jianping Huang, Xiao-hui Fan, 2010, Comput. Biol. Medicine.

Selecting a single model or combining multiple models for microarray-based classifier development? – A comparative analysis based on large and diverse datasets generated from the MAQC-II project

Weida Tong, Leming Shi, Hong Fang, 2011, BMC Bioinformatics.

Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS)

Weida Tong, Huixiao Hong, Leming Shi, 2005, BMC Bioinformatics.

ArrayTrack: An FDA and Public Genomic Tool.

Weida Tong, Leming Shi, Hong Fang, 2017, Methods in molecular biology.

Two new ArrayTrack libraries for personalized biomedical research

Weida Tong, Huixiao Hong, Hong Fang, 2010, BMC Bioinformatics.

Study of serious adverse drug reactions using FDA-approved drug labeling and MedDRA

Stephen C. Harris, W. Tong, H. Fang, 2019, BMC Bioinformatics.

A phenome-guided drug repositioning through a latent variable model

W. Tong, H. Fang, R. Kelly, 2014, BMC Bioinformatics.

A phenome-guided drug repositioning through a latent variable model

Xiaowei Xu, Weida Tong, Hong Fang, 2014, BMC Bioinformatics.

Differential gene expression in mouse primary hepatocytes exposed to the peroxisome proliferator-activated receptor α agonists

Weida Tong, Leming Shi, Hong Fang, 2006, BMC Bioinformatics.

QSARs for Endocrine Disruption Priority Setting Database 2: The Integrated 4‐Phase Model

Weida Tong, Hong Fang, Roger Perkins, 2003 .

In vitro to in vivo extrapolation for drug-induced liver injury using a pair ranking method.

Weida Tong, Hong Fang, Zhichao Liu, 2017, ALTEX.

Gaining Confidence on Molecular Classification through Consensus Modeling and Validation

Huixiao Hong, Weida Tong, Roger Perkins, 2006, Toxicology mechanisms and methods.

University of Birmingham The Liver Toxicity Knowledge Base (LKTB) and Drug-Induced Liver Injury (DILI) classification for assessment of human liver injury

H. Fang, Minjun Chen, Zhichao Liu, 2017 .

Investigation of reproducibility of differentially expressed genes in DNA microarrays through statistical simulation

Weida Tong, Leming Shi, Hong Fang, 2009, BMC proceedings.

Multiclass Decision Forest--a novel pattern recognition method for multiclass classification in microarray data analysis.

Leming Shi, W. Tong, H. Fang, 2004, DNA and cell biology.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

Todd H. Stokes, Kevin C. Dorff, Aaron M. Smalter, 2010, Nature Biotechnology.

Assessment of Prediction Confidence and Domain Extrapolation of Two Structure–Activity Relationship Models for Predicting Estrogen Receptor Binding Activity

Weida Tong, Qian Xie, Huixiao Hong, 2004, Environmental health perspectives.

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.

W. Tong, H. Fang, H. Hong, 2015, Toxicological sciences : an official journal of the Society of Toxicology.

In silico drug repositioning: what we need to know.

W. Tong, H. Fang, W. Slikker, 2013, Drug discovery today.