Bioinformatics and Biostatistics
Meet the Division Director: Weida Tong, Ph.D.
Dr. Tong's career has been dedicated to leadership in developing and applying bioinformatics, chemoinformatics, and computational methods in the areas of systems biology, predictive toxicology, and clinical application. He serves as a Science Advisory Board (SAB) member for several large initiatives involving multiple institutes within Europe and the U.S. He also holds several adjunct positions at U.S. universities. His division at FDA’s National Center for Toxicological Research spans, IT, software development, biostatistics, as well as bioinformatics research focusing on methodologies and standards to advance a diversity of areas in regulatory science and precision medicine. Some particularly visible research areas currently are:
- The Microarray/Sequencing Quality Control (MAQC/SEQC) consortium to develop standard analyses protocols and quality control metrics for emerging technologies for regulatory science and precision medicine applications.
- Further development of the Liver Toxicity Knowledge Base (LTKB) for drug safety evaluation.
- In silico drug repositioning for the enhanced treatment of rare or orphaned diseases.
- Development of the FDA bioinformatics system, ArrayTrackTM suite, software used for FDA review and research in pharmacogenomics. In addition, the division also specializes in molecular modeling and QSARs, with current activities involving estrogen, androgen, and endocrine active compound screening. His research (>200 publications) is cataloged in prominent peer-reviewed journals.
The Division of Bioinformatics and Biostatistics develops integrated bioinformatics and biostatistics capability to address increasing needs in biomarker development, drug safety, drug repositioning, personalized medicine, and risk assessment.
The Division is comprised of four branches:
- Bioinformatics—research efforts focused on predictive toxicology, precision medicine, biomarker development, drug safety, and drug repositioning. Most research projects are in collaboration with scientists within NCTR, across FDA Product Centers, and in the larger scientific community. One of the key endeavors is to construct knowledge bases in the specific areas of FDA’s responsibility to provide a data-driven decision-making environment for enhanced safety evaluation and precision medicine.
- Biostatistics—conducts peer-reviewed research of statistical methods to analyze toxicological and molecular data as well as data-mining techniques for pattern identification and signal detection. The branch also provides statistical support related to FDA’s mission to protect and promote public health.
- Scientific Computing—provides critical support and enhancement to infrastructure in the areas of software and database development for research support and research management, high performance computing, systems integration, and information system asset management and procurement.
- R2R (review-to-research and return)—strengthens the division, focuses on “knowledge uptake” of the Division’s research products for regulatory application, and enables “data liberation” of regulatory data from the FDA Product Centers. Thus, facilitating regulatory-science research in the Division and increasing NCTR's linkages with FDA Product Centers.
NCTR Bioinformatic Tools
- ArrayTrack™ HCA-PCA Standalone Package
Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) powerful data-exploring tools extracted from ArrayTrack™
- The de novo Assembly Quality Evaluation Tool (dnAQET)
Framework designed to evaluate the contigs of a de novo assembly against a trusted reference genome
- Decision Forest
A novel pattern recognition method for analysis of data from microarray experiments, proteomics research, and predictive toxicology
- Estrogenic Activity Database (EADB)
Comprehensive set of estrogenic activity data from a variety of data sources and a component of the enhanced Endocrine Disruptors Knowledge Base (EDKB)
- Endocrine Disruptor Knowledge Base (EDKB)
Scientific resources to predict estrogen and androgen activity
Full-Text Search of Product Labeling
- Liver Toxicity Knowledge Base (LTKB)
Collection of diverse drug-induced liver injury data associated with individual drugs and development of predictive models to assess risk of drug-induced liver injury
- MicroArray/Sequencing Quality Control (MAQC/SEQC) Project
Development of microarray quality control metrics and thresholds
Generate molecular descriptors from two-dimensional structures
- NCTR Liver Cancer Database (NCTRlcdb)
Database of 999 chemicals with assigned liver-toxicity classifications to facilitate the construction of cleaner and better carcinogenicity models by FDA and other organizations
For more information, please contact Weida Tong, Ph.D. at 870-543-7142 or firstname.lastname@example.org.