A photo of Jing Chen.

Jing Chen, PhD

  • Assistant Professor, UC Department of Pediatrics
  • UC Department of Biomedical Informatics



My research areas involve genetics of preterm birth, phenomics for common and rare disorders, and genomics of pediatric cancers and congenital heart defects.

The goals I’m attempting to achieve in my research are: 1) developing computational processes to use electronic health records for the phenomics of genetic disorders and 2) developing analytics systems and algorithms to detect pathogenic genetic variants and improve our understanding of the etiology.

I have always enjoyed working with and managing big data. I am also happy to help patients, especially children. My career allows me to combine these interests and pursue biomedical informatics research. Along with my work as a data scientist, I am also an assistant professor at the University of Cincinnati.

One of my notable achievements is the development of computational methods and the web application of the ToppGene suite. I completed this work while pursuing my PhD under the mentorship of Drs. Bruce Aronow and Anil Jegga. The research community has welcomed this research and has appreciated the ToppGene publications and the application. These publications have had more than 2,000 citations.

When working as a researcher with Dr. Mario Medvedovic at the University of Cincinnati, we designed a statistical framework to link transcription factors with conditions and medications based on ChIP-seq and mRNA expression data. At Cincinnati Children’s Hospital Medical Center, with the help of Dr. Ge Zhang, I developed GDDP, which is an innovative phenotype-disease matching tool for rare genetic disorders. Our research also laid the groundwork for using electronic medical records to prioritize genetic disorders. Also, with Dr. Ge Zhang, we recently published a genetic study to understand the contribution of maternal and fetal genetic effects towards the associations between maternal phenotypes and birth outcomes.

I have more than 10 years’ experience in the biomedical informatics field and started working at the Cincinnati Children’s Hospital Medical Center in 2015. My research has been published in numerous journals including Genetics in Medicine, PLOS Medicine, Scientific Reports and Nucleic Acids Research.

BS: National University of Singapore, Singapore, 2002.

PhD: University of Cincinnati, Cincinnati, OH, 2008.


Rare genetic disease; clinical NGS


Phenomics for common and rare diseases; genetics of preterm birth; genomics of pediatric cancers.

Research Areas

Biomedical Informatics



Dissecting maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes, and adult phenotypes: A mendelian-randomization and haplotype-based genetic score analysis in 10,734 mother-infant pairs. Chen, J; Bacelis, J; Sole-Navais, P; Srivastava, A; Juodakis, J; Rouse, A; Hallman, M; Teramo, K; Melbye, M; Feenstra, B; et al. PLoS Medicine. 2020; 17:e1003305.


Novel phenotype-disease matching tool for rare genetic diseases. Chen, J; Xu, H; Jegga, A; Zhang, K; White, PS; Zhang, G. Genetics in Medicine. 2019; 21:339-346.


Genome-wide signatures of transcription factor activity: connecting transcription factors, disease, and small molecules. Chen, J; Hu, Z; Phatak, M; Reichard, J; Freudenberg, JM; Sivaganesan, S; Medvedovic, M. PLoS Computational Biology. 2013; 9:e1003198.


Disease candidate gene identification and prioritization using protein interaction networks. Chen, J; Aronow, BJ; Jegga, AG. BMC Bioinformatics. 2009; 10:73.


ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Chen, J; Bardes, EE; Aronow, BJ; Jegga, AG. Nucleic Acids Research. 2009; 37:W305-W311.


Improved human disease candidate gene prioritization using mouse phenotype. Chen, J; Xu, H; Aronow, BJ; Jegga, AG. BMC Bioinformatics. 2007; 8:392.

Association of maternal prenatal copper concentration with gestational duration and preterm birth: a multicountry meta-analysis. Monangi, NK; Xu, H; Fan, Y; Khanam, R; Khan, W; Deb, S; Pervin, J; Price, JT; Kaur, L; INTERBIO-21st Study Consortium, ; et al. American Journal of Clinical Nutrition. 2024; 119:221-231.

A functional mechanism for a non-coding variant near AGTR2 associated with risk for preterm birth. Wang, L; Rossi, RM; Chen, X; Chen, J; Runyon, J; Chawla, M; Miller, D; Forney, C; Lynch, A; Zhang, X; et al. BMC Medicine. 2023; 21:258.

Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth. Beaumont, RN; Flatley, C; Vaudel, M; Wu, X; Chen, J; Moen, GH; Skotte, L; Helgeland, Ø; Solé-Navais, P; Banasik, K; et al. Nature Genetics. 2023; 55:1807-1819.

Lipocalin 10 is essential for protection against inflammation-triggered vascular leakage by activating LDL receptor-related protein 2-slingshot homologue 1 signalling pathway. Zhao, H; Wang, P; Wang, X; Du, W; Yang, HH; Liu, Y; Cui, SN; Huang, W; Peng, T; Chen, J; et al. Cardiovascular Research. 2023; 119:1981-1996.