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Presence Current · Arkansas
Last published 2026
Sources OpenAlex · ORCID
Refreshed 2026-10-06

Baitang Ning

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Also affiliated: Qingdao University (2020); United States Department of Health and Human Services (2010–2012); United States Food and Drug Administration (2006–2026); Chinese Academy of Medical Sciences & Peking Union Medical College (2007); First Affiliated Hospital of Guangzhou Medical University (2021); National Cancer Institute (2021); Cancer Hospital of Chinese Academy of Medical Sciences (2007); State Key Laboratory of Respiratory Disease (2021); Guangzhou Institute of Respiratory Health (2021); Western University of Health Sciences (2008)

44 h-index 164 pubs 11,273 cited

  • Humans
  • Polymorphism, Single Nucleotide
  • MicroRNAs
  • Animals
  • Hep G2 Cells
  • Gene Expression Profiling
  • Hepatocytes
  • High-Throughput Nucleotide Sequencing
  • Cell Line
  • Genetic Predisposition to Disease
  • Sequence Analysis, RNA
  • Male
  • Female
  • RNA, Messenger
  • Liver

Biography and Research Information

OverviewAI-generated summary

Baitang Ning's research focuses on the application and evaluation of high-throughput molecular profiling technologies, particularly in the context of toxicological research and predictive modeling. Ning has been involved in significant consortia, including the MicroArray Quality Control (MAQC) project and the Sequencing Quality Control (SQC) Consortium, which aimed to assess the reproducibility and accuracy of gene expression measurements from microarray and RNA sequencing platforms. These projects have generated substantial data on common practices for developing and validating predictive models based on these technologies.

Further investigations have explored the accuracy, reproducibility, and information content of RNA-sequencing technologies, including single-cell RNA-seq. Ning's work also extends to comparing different profiling methods, such as RNA-seq and microarray-based models, for their utility in clinical endpoint prediction. Additionally, research has examined the expression of drug-metabolizing enzymes in human hepatic cell lines and primary hepatocytes, and investigated functional genetic variants associated with disease risk, such as cyclooxygenase-2 and esophageal cancer.

Ning has a notable publication record with 167 total publications and over 11,000 citations, reflected in an h-index of 45. Key collaborators include Joe Meehan, Bohu Pan, and Weigong Ge, with whom Ning has co-authored numerous publications at the National Center for Toxicological Research.

Metrics

  • h-index: 44
  • Publications: 164
  • Citations: 11,273

Selected Publications

  • SARS-CoV-2 Spike Protein’s Structural Dynamics Affect the Activity of the Bebtelovimab Antibody (2026)
    Journal of Chemical Information and Modeling DOI OpenAlex
  • Microphysiological systems as an emerging in vitro approach for the evaluation of drug absorption, distribution, metabolism, and excretion and toxicity (2025)
    Drug Metabolism and Disposition 11 citations DOI OpenAlex
  • Identification of Genetic Risk Factors Associated With Herbal and Dietary Supplement–Induced Acute Liver Failure Using Whole Exome Sequencing Analysis (2025)
    Gastro Hep Advances DOI OpenAlex
  • DILIrank dataset for QSAR modeling of drug-induced liver injury (2023)
    Elsevier eBooks DOI OpenAlex
  • Pharmacological Effects of Ketoconazole in the Treatment of Steroidogenesis Suppression via CYP17A1 Inhibition May Involve MicroRNA Regulation (2023)
    Journal of Pharmacology and Experimental Therapeutics 1 citation DOI OpenAlex
  • Additional file 3 of Assessing reproducibility of inherited variants detected with short-read whole genome sequencing (2022)
    Figshare DOI OpenAlex
  • Additional file 13 of Assessing reproducibility of inherited variants detected with short-read whole genome sequencing (2022)
    Figshare DOI OpenAlex
  • Additional file 5 of Assessing reproducibility of inherited variants detected with short-read whole genome sequencing (2022)
    Figshare DOI OpenAlex
  • Additional file 15 of Assessing reproducibility of inherited variants detected with short-read whole genome sequencing (2022)
    Figshare DOI OpenAlex
  • Additional file 10 of Assessing reproducibility of inherited variants detected with short-read whole genome sequencing (2022)
    Figshare DOI OpenAlex
  • Additional file 9 of Assessing reproducibility of inherited variants detected with short-read whole genome sequencing (2022)
    Figshare DOI OpenAlex
  • Additional file 11 of Assessing reproducibility of inherited variants detected with short-read whole genome sequencing (2022)
    Figshare DOI OpenAlex
  • Additional file 1 of Assessing reproducibility of inherited variants detected with short-read whole genome sequencing (2022)
    Figshare DOI OpenAlex
  • Additional file 6 of Assessing reproducibility of inherited variants detected with short-read whole genome sequencing (2022)
    Figshare DOI OpenAlex
  • Additional file 12 of Assessing reproducibility of inherited variants detected with short-read whole genome sequencing (2022)
    Figshare DOI OpenAlex

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Collaboration Network

538 Collaborators 193 Institutions 21 Countries

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