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  8. Binsheng Gong
  1. Science & Research (NCTR)

Binsheng Gong Ph.D.

Bioinformatician — Division of Bioinformatics and Biostatistics (Review-to-Research and Return Branch)

Binsheng Gong
Binsheng Gong, Ph.D.

(870) 543-7121
NCTRResearch@fda.hhs.gov  

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 About  |  Publications 


Background

Dr. Binsheng Gong received a bachelor’s degree in medicine and a Ph.D. in biophysics from Harbin Medical University, China. He joined Harbin Medical University as a teaching and research assistant, then lecturer and associated professor.

In 2012, Dr. Gong started his research at FDA’s National Center for Toxicological Research (NCTR) as a postdoctoral research scholar before becoming a staff fellow. Since starting at NCTR, Dr. Gong has served as one of the major investigators of the FDA-led Sequencing Quality Control (SEQC) Phase 1 and 2 projects. The SEQC/SEQC2 projects assess the technical performance of next-generation sequencing platforms by generating benchmark datasets with reference samples and evaluating advantages and limitations of various bioinformatics strategies in RNA and DNA analyses. The projects have resulted in more than thirty publications in scientific journals. Dr. Gong was the lead author of several manuscripts in Nature Biotechnology and Genome Biology and co-authored several other manuscripts.

As mentioned in Nature Biotechnology, “These large-scale coordinated efforts signal that the RNA-seq field is moving one step closer to clinical application by establishing standards for assessing analytical validity” and, “The studies from the SEQC Consortium provide an important milestone in a longer path to develop laboratory tests that have analytical and clinical utility.” Former Deputy FDA Commissioner Dr. Janet Woodcock highlighted the contribution of the MAQC consortium effort to the precision medicine in a comment published in Nature Biotechnology. Dr. Gong has also been involved in the Liver Toxicity Knowledge Base project by studying drug safety with specific emphasis on drug-induced liver injury (DILI). Building on the big success of SEQC project and other projects he has been involved in, Dr. Gong now continues his research on the second phase of the project (SEQC II) and small RNA toxicity studies.

Dr. Gong has received several FDA and NCTR Awards, including FDA Excellence in Analytical Science (2022), FDA Scientific Achievement Award (2015), NCTR Special Act or Service Award (2023), NCTR Director’s Publication Award for Data (2022), NCTR Group Recognition Award (2021, 2017), NCTR Special Act Award (2020, 2018, 2017), NCTR Chief Scientist Publication Award for Data Methods, Analysis, and Study Design (2016), NCTR Scientific Achievement Award: Excellence in Analytical Science (2015).


Research Interests

Dr. Gong has more than 15 years of distinguished research and education experience and a record of exceptional scientific accomplishments in the field of bioinformatics with emphasis on:

  • Next-generation sequencing (NGS)
  • Microarray technologies
  • Biological/medical “big data” mining
  • Data interpretation


Biological/medical “big data” mining incorporates personal genomic/transcriptomic data, clinical data, and other data generated from high-throughput technologies. Data mining and interpretation develops and uses methods, software, and workflows to manage and analyze the “big data” and to interpret the biological/clinical meanings by integrating data and knowledge bases. This research supports basic biological study and translational medicine as well as drug development and drug-safety investigation.

Dr. Gong’s current research interests include:

  • Examining the emerging technologies, particularly on NGS, to understand the impact of technical issues and bioinformatics methods
  • Evaluating the utility of these emerging technologies and methods in clinical and safety assessments with quality-control matrix and procedures
  • Biomarker identification for DILI and predictive toxicity, using data-mining methodology and systems-biology strategies
  • Developing standard operating procedures for NGS applications, such as ultralow-frequency mutations detection by duplex sequencing, biomarker identification by RNA sequencing, and small RNA sequencing
  • Genome-wide identification and characterization of circular RNAs and novel microRNAs for human, monkey, mouse, and rat


Select Publications

Evaluating the Analytical Validity of Circulating Tumor DNA Sequencing Assays for Precision Oncology.
Deveson I.W., Gong B., Lai K., LoCoco J.S., Richmond T.A., et al. and the SEQC2 Oncopanel Sequencing Working Group.
Nature Biotechnology. 2021, 39:1115–1128.

Cross-Oncopanel Study Reveals High Sensitivity and Accuracy with Overall Analytical Performance Depending on Genomic Regions.
Gong B., Li D., Kusko R., Novoradovskaya N., Zhang Y., et al. 
Genome Biology. 2021: 22(1):109.

A Verified Genomic Reference Sample for Assessing Performance of Cancer Panels Detecting Small Variants of Low Allele Frequency.
Jones W., Gong B., Novoradovskaya N., Li D., Kusko R., et al.
Genome Biology. 2021, 22(1):111.

Mechanistic Roles of MicroRNAs in Hepatocarcinogenesis: A Study of Thioacetamide with Multiple Doses and Time-Points of Rats.
Dweep H., Morikawa Y., Gong B., Yan J., Liu Z., Chen T., Bisgin H., Zou W., Hong H., Shi T., Gong P., Castro C., Uehara T., Wang Y., and Tong W.
Scientific Reports. 2017, 7(1):3054.

The FDA's Experience with Emerging Genomics Technologies-Past, Present, and Future.
Xu J., Thakkar S., Gong B., and Tong W.
AAPS Journal. 2016, 18(4):814-8.

Comprehensive Assessments of RNA-Seq by the SEQC Consortium: FDA-Led Efforts Advance Precision Medicine.
Xu J., Gong B., Wu L., Thakkar S., Hong H., and Tong W.
Pharmaceutics. 2016, 8(1).

Discovering Functional Modules by Topic Modeling RNA-Seq Based Toxicogenomic Data.
Yu K., Gong B., Lee M., Liu Z., Xu J., Perkins R., and Tong W.
Scientific Reports. 2014, 27(9):1528-36.

The Concordance Between RNA-Seq and Microarray Data Depends on Chemical Treatment and Transcript Abundance.
Wang C., Gong B., Bushel P., Thierry-Mieg J., Thierry-Mieg D., Xu J., Fang H., Hong H., Shen J., Su Z., Meehan J., Li X., Yang L., Li H., Labaj P., Kreil D., Megherbi D., Gaj S., Caiment F., van Delft J., Kleinjans J., Scherer A., Devanarayan V., Wang J., Yang Y., Qian H., Lancashire L., Bessarabova M., Nikolsky Y., Furlanello C., Chierici M., Albanese D., Jurman G., Riccadonna S., Filosi M., Visintainer R., Zhang K., Li J., Hsieh J., Svoboda D., Fuscoe J., Deng Y., Shi L., Paules R., Auerbach S., and Tong W.
Nature Biotechnology. 2014, 32: 926-932.

A Comprehensive Assessment of RNA-Seq Accuracy, Reproducibility and Information Content by the Sequencing 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 L.J., Bessarabova M., Yang X., Ning B., Gong B., Meehan J., Xu J., Ge W., Perkins R., Fischer M., and Tong W.
Genome Biology. 2014, 15(12):523.


Contact Information
Binsheng Gong
(870) 543-7121
Expertise
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