Staff Fellow — Division of Bioinformatics and Biostatistics

Xi Chen, Ph.D.
(870) 543-7121
NCTRResearch@fda.hhs.gov  

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About  |  Publications

Background

Dr. Xi Chen received a Bachelor of Science degree in bioinformatics, a Master of Science degree in biomedical engineering, and a Ph.D. in medicine from Harbin Medical University, China. She worked as a lecturer at Harbin Medical University, where she was responsible for teaching courses, conducting research, and advising students. Dr. Chen has extensive research experience, having worked on cellular reprogramming, RNA-sequencing analysis, microarray analysis, microRNA research, and biomolecular network reconstruction. She has taught various courses such as Operations Research, Mathematical Modeling, C Programming Language, MATLAB, and R Programming and Bioconductor, among others, to undergraduate and seven-year program students. She mentored undergraduate students and teams in the China Undergraduate Mathematical Contest in Modeling, was a research manager and undergraduate counselor at the College of Bioinformatics Science and Technology at Harbin Medical University, and served as secretary of the Chinese Conference on Bioinformatics & Systems Biology.

Dr. Chen worked as a program participant through the Oak Ridge Institute for Science and Education (ORISE) at FDA’s National Center for Toxicological Research (NCTR). She joined the Division of Bioinformatics and Biostatistics at NCTR as an ORISE fellow in 2020 and became a staff fellow in 2022. She has more than 20 peer-reviewed publications and one patent. During her time at NCTR, she has been recognized with several awards, including:

• FDA Scientific Achievement Award for Outstanding Intercenter Scientific Collaboration (2021)
• FDA NCTR Special Act Award (2022)
• Top 5 selected posters at FDA Scientific Computing Days (2022)
• Top 20 selected posters at FDA Scientific Computing Days (2021)
• First-Place Postdoc Winner of the Best Oral Presentation Award at the Drug Discovery and Development Colloquium (2021)
• First-Place Postdoc Winner of the MCBIOS Young Scientist Excellence Award at the MidSouth Computational Biology and Bioinformatics Society (MCBIOS) & MicroArray Quality Control joint conference (2021)
• Second-Place Winner of the annual Environment Mutagenesis and Genomics Society’s Bioinformatics Challenge (2022)
• Second-Place Postdoc Winner of the MCBIOS Young Scientist Excellence Award at the 18th Annual Conference (2022)
  
   

Research Interests

Dr. Chen is an accomplished researcher with over a decade of experience in bioinformatics, molecular biology, and developmental biology. With her cross-disciplinary training, she possesses in-depth knowledge of bioinformatics and biostatistics tools, databases, medicine, and biology. Her research interests focus on developing statistical and computational methods to integrate multi-omics data, identify functional variants, and discover biomarkers, with the aim of interpreting medical big data and obtaining a novel and insightful understanding of their biological and clinical significance at the molecular level. She is also interested in using data mining methods and systems-biology strategies for both basic biological research and translational medicine investigations.

Recently, Dr. Chen has been exploring the use of artificial intelligence (AI) as an alternative method to animal studies. She is developing generative AI frameworks to advance safety assessment in the field of pharmacovigilance and toxicology without using animal testing. With the wealth of animal data available, generative AI offers a promising approach to simulating virtual animal experiments, generating multi-dimensional profiles similar to traditional animal studies, and approximating populations of diverse individual animals. This can help to improve the accuracy of toxicity prediction, enhance the translation of animal data to human outcomes, as well as reduce the need for animal testing in drug development. Dr. Chen's expertise and research interests are aimed at advancing the use of big data and artificial intelligence in biomedical research, with the ultimate goal of improving human health.

Professional Societies/National and International Groups

MidSouth Computational Biology and Bioinformatics Society
Member
2021 – Present

Selected Publications

Tox-GAN: An Artificial Intelligence Approach Alternative to Animal Studies—A Case Study With Toxicogenomics.
Chen X., Roberts R., Tong W., and Liu Z.
Toxicol Sci. 2022, 186(2):242-259.

AI-Powered Drug Repurposing for Developing COVID-19 Treatments.
Liu Z., Chen X., Carter W., Moruf A., Komatsu T.E., Pahwa S., Chan-Tack K., Snyder K., Petrick N., Cha K., Lal-Nag M., Hatim Q., Thakkar S., Lin Y., Huang R., Wang D., Patterson T.A., and Tong W.
Reference Module in Biomedical Sciences. 2022, B978-0-12-824010-6.00005-8.

Unraveling Gene Fusions for Drug Repositioning in High-Risk Neuroblastoma.
Liu Z., Chen X., Roberts R., Huang R., Mikailov M., and Tong W. 
Front Pharmacol. 2021, 12:608778.

DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction.
Bhatt A., Roberts R., Chen X., Li T., Connor S., Hatim Q., Mikailov M., Tong W., and Liu Z.
Front Artif Intell. 2021, 4:711467.

AI-Based Language Models Powering Drug Discovery and Development.
Liu Z., Roberts R.A., Lal-Nag M., Chen X., Huang R., and Tong W.
Drug Discov Today. 2021, 26(11):2593-2607.