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  1. Science & Research (NCTR)

Hong Fang Ph.D.

Research Biologist — Office of Scientific Coordination

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Hong Fang, Ph.D.
(870) 543-7391
NCTRResearch@fda.hhs.gov  

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About  |  Publications 


Background

Dr. Hong Fang received her bachelor’s degree in chemistry in 1983, followed by her master’s degree in chemistry in 1986 from Fudan University in Shanghai, China. In 1995 she received her Ph.D. degree in chemistry from the University of Missouri, St. Louis. After graduation Dr. Fang worked for the St. Louis County Police Department Crime Laboratory as a forensic scientist. In 1997 she was hired by NCTR as a postdoctoral fellow. In 2000 she took a position as a contractor for Northrop Grumman Information Technology working as an NCTR senior computational scientist until 2004 when she was hired as a contractor for Z-Tech Corporation as a senior bioinformatician at NCTR. In 2008, Dr. Fang was appointed by ICF International as director for their NCTR Bioinformatics Group contracted by NCTR. In 2012 Dr. Fang was hired as a full-time FDA employee and has served as a senior bioinformatician and project manager for NCTR.  Additionally, since 2016 she has served as an adjunct professor of the Department of Information Science for the University of Arkansas at Little Rock.  Dr. Fang has received many awards over the years including:

  • 2016 – “Outstanding Inter-center Scientific Collaboration” Group Recognition Award for FDALabel team from FDA/HHS, cited as “Developed a bioinformatics tool and relational database for FDA drug labeling to aid regulatory decision making and drug review in advancing translational and regulatory sciences”
  • 2016 – Commissioner’s Special Citation “Research to the Review and Return (R2R) Team for a Cross Center Bioinformatics Projects Benefiting Regulatory Business Processes” Group Recognition Award from FDA.
  • 2016 – Chief Scientist Publication Award for “DataMethods/Analysis/Study Design” (Group)
  • 2015 – FDA Chief scientist publication award for basic, translational or applied science
  • 2015 – NCTR Scientific Achievement Award – Excellence in Analytical Science (Group)/FDA Team of the Sequencing Quality Control project
  • 2013 – FDA Group Recognition (Crosscutting) “For intercenter development of a custom microarray genomics pipeline for food borne enteric pathogen outbreak investigations”
  • 2009 – Z-Tech/ICF International Bioinformatics Group, Group Recognition Award from FDA/HHS. for the achievement in development a suite of  NCTR bioinformatics tools
  • 2009 – The FDA MicroArray Quality Control (MAQC) Project Committee, Leveraging Collaboration Award FDA
  • 2005 – NCTR ArrayTrack Development Team, Commissioner’s Special Citation awarded by FDA

Research Interests

Dr. Fang’s research interest is to apply bioinformatics, chemoinformatics, knowledge base and big data methodologies, and predictive toxicology approaches to address issues in the areas of:

  • toxicology
  • clinical application
  • data-oriented researches (data science)
  • adverse drug reaction (ADR)
  • pharmacogenomics and precision medicine
  • biomarker development and application

Dr. Fang has over 15 years of experience applying data mining, pattern recognition, machine learning, classification, molecular modeling, bioinformatics, and chemoinformatics approaches in these areas. Her research experience is broad, ranging from applying bioinformatics methods to studying specific diseases and toxicity to managing and coordinating large software development programs. For example, Dr. Fang developed integrated bioinformatics approaches for biomarker discovery for lupus, chronic fatigue syndrome, drug-induced liver injury, cancer, brain function, and more. Currently, she is leading an effort to develop an FDALabel database — a web-based application — to mine FDA drug labeling data. One effort in this project is to integrate FDA labeling data with various medical ontologies, such as MedDRA (Medical Dictionary for Regulatory Application) and UMLS (Unified Medical Language System) for enhance the use of drug labeling data and its readiness for integration with other FDA databases like the FDA Adverse Event Reporting System.

As a senior bioinformatician and project manager within NCTR’s Office of Scientific Coordination she leads several large bioinformatics projects. For example, leading and coordinating efforts that have resulted in widely used software to support FDA‘s genomic research and review, study of adverse drug reaction (ADR), and precision medicine.  Some of the bioinformatics tools that she helped develop can be found at www.fda.gov/nctrbioinformatics and examples include:

  • FDALabel: a full-text search web-based database of the FDA drug labeling system which is a resource in study of drug safety, pharmacovigilance, and precision medicine
  • ArrayTrack: an integrated genomics tool to support FDA review and research on genomics and pharmacogenomics
  • LTKB (Liver Toxicity Knowledge Base): a collection of diverse drug-induced liver injury data to assess risk of drug-induced liver injury
  • EDKB (Endocrine Disruptor Knowledge Base): an integrated database to prioritize chemicals for potential endocrine disruption
  • EMEN2 (Electron Microscopy Electronic Notebook): An in-house database to manage images and nano-toxicological studies and bio-images at NCTR.

Dr. Fang has mentored and supervised many young scientists, postdoctoral fellows, and summer interns (one student each year for five consecutive years). She also has many publications that are widely recognized with high citations (a total of 9036 citations from 143 manuscripts and an H-Index of 43, as Aug. 16, 2016, from Google Scholar Citations).

Professional Societies/National and International Groups

Journal of Frontiers in Neurology
Editorial Board Member
2014 – Present

MidSouth Computational Biology & Bioinformatics Society (MCBIOS)
Member
2008 – Present

Society of Toxicology (SOT)
Member
2008 – Present

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Select Publications

Publication titles are linked to text abstracts on PubMed.

Potential Reuse of Oncology Drugs in the Treatment of Rare Diseases.
Liu Z, Fang H, Slikker W, Tong W.
Trends in Pharmacological Sciences. 2016. 843–857.
 

FDA Drug Labeling: Rich Resources to Facilitate Precision Medicine, Drug Safety, and Regulatory Science.
Fang H, Harris S, Liu Z, Zhou G, Zhang G, Xu J, Howard P, Tong W.
Drug Discovery Today. 2016. 21(10): 1566-1570.
 

Exploring the FDA Adverse Event Reporting System to Generate Hypotheses for Monitoring of Disease Characteristics.
Fang H, Su Z, Wang Y, Miller A, Liu Z, Howard P, Tong W, Lin SM.
Clinical Pharmacology & Therapeutics. 2014. 95(5):496-498.
 

A Comprehensive Assessment of RNA-Seq Accuracy, Reproducibility and Information Content by the Sequence Quality Control Consortium.
SEQC/MAQC-III Consortium.
Nature Biotechnology. 2014. 32, 903–914.
 

An Investigation of Biomarkers Derived from Legacy Microarray Data for their Utility in the RNA-Seq Era.
Su Z, Fang H, Hong H, Shi L, Zhang W, Zhang W, Zhang Y, Dong Z, Lancashire LJ, Bessarabova M.
Genome biology. 2014. 15(12):1.
 

Towards Interoperable Bioscience Data.
Sansone SA, Rocca-Serra P, Field D, Maguire E, Taylor C, Hide W, Hofmann O, Fang H, Neumann S, Tong W.
Nature Genetics. 2012. 44(2):121-126.
 

Next-Generation Sequencing and its Applications in Molecular Diagnostics.
Su Z, Ning B, Fang H, Hong H.
Molecular Diagnostics. 2011. 11(3):333-343.
 

Metaanalysis of Lupus Microarray Data Using a Novel Pathway-Based Approach.disclaimer icon
Arasappan D, Tong W, Siegel J, Mummaneni P, Fang H, Amur S.
BMC Medicine. 2011. 9:65.
 

An FDA Bioinformatics Tool for Microbial Genomics Research on Molecular Characterization of Bacterial Foodborne Pathogens Using Microarrays.
Fang H, Xu J, Ding D, Jackson S, Patel I.
BMC Bioinformatics. 2010. 11(Suppl 6):S4.
 

The MAQC-II Project: A Comprehensive Study of Common Practices for the Development and Validation of Microarray-Based Predictive Models.
The MAQC Consortium.
Nature Biotechnology. 2010. 28:827–838.
 

GOFFA: Gene Ontology For Functional Analysis- Software for Gene Ontology-Based Functional Analysis of Genomic and Proteomic Data.
Sun H, Fang H, Chen T, Perkins R, Tong W.
BMC Bioinformatics. 2006. 7(Suppl 2):S23.
 

The MicroArray Quality Control (MAQC) Project Shows Inter- and Intraplatform Reproducibility of Gene Expression Measurements.
The MAQC Consortium.
Nature Biotechnology. 2006. 24(9) and 24(10s):1151-1161.
 

Performance Comparison of One-Color and Two-Color Platforms Within the Microarray Quality Control (MAQC) Project.
Patterson T, Lobenhofer E, Fulmer-Smentek S, Collins J, Chu T, Bao W, Fang H.
Nature Biotechnology. 2006. 24(9) and 24(10s):1140–1150.
 

Gene Expression Profile Exploration of a Large Dataset on Chronic Fatigue Syndrome.
Fang H, Xie Q, Boneva R, Fostel J, Perkins R, Tong W.
Pharmacogenomics. 2006. 7(3).
 

Bioinformatics Approaches for Cross-Species Liver Cancer Analysis Based on Microarray Gene Expression Profiling.
Fang H, Tong W, Perkins R, Shi L, Hong H, Cao X, Xie Q, Yim S, Ward J, Pitot H.
BMC bioinformatics. 2005. 6(2):1.
 

ArrayTrack-Supporting Toxicogenomic Research at the FDA’s National Center for Toxicological Research (NCTR).
Tong W, Cao X, Harris S, Sun H, Fang H, James Fuscoe, Harris A, Hong H, Xie Q, Perkins R, Shi L, Casciano D.
EHP Toxicogenomics. 2003. 111(15):1819-1826.
 

Structure-Activity Relationships of 202 Natural, Synthetic and Environmental Chemicals Binding to Androgen Receptors.
Fang H, Tong W.
Chem Res Toxicol. 16(10):1338-58, 2003.
 

Decision Forest: Combining the Predictions of Multiple Independent Decision Tree Models.
Tong W, Hong H, Fang H, Xie Q, Perkins R.
 J. Chem. Info. Comp. Sci. 2003. 43(2):525 – 531.
 

Structure-Activity Relationship for a Large Diverse Set of Natural, Synthetic and Environmental Chemicals.
Fang H, Tong W, Shi L, Blair R, Perkins R, Branham W, Dial S, Moland C, Sheehan, D.
Chemical Research in Toxicology. 2001. 14:280–294.
 

Quantitative Comparison of In Vitro Assays for Estrogenic Activity.
Fang H, Tong W, Perkins R, Soto A, Prechtl N, Sheehan, D.
Environmental Health Perspectives. 2000. 108:723–729.
 

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Contact Information
Hong Fang
(870) 543-7391
Expertise
Expertise
Approach
Domain
Technology & Discipline
Toxicology