A photo of Bruce Aronow.

Bruce J. Aronow, PhD

  • Co-director, Computational Medicine Center
  • Professor, UC Department of Pediatrics



I first became a researcher because of my continuous curiosity; I find satisfaction in learning how things work.

Decades later, I’m still sustained by figuring out how to lessen the burdens of disease. As a computational biologist, I have a passion for accelerating discoveries from any biomedical research area that provides an understanding of how life works and how healthy functions are achieved.

I’ve analyzed many different types of data, developed algorithms, and built websites and databases. These tools allow researchers from varying disciplines and backgrounds to analyze genetic and genomic data — either their own or that gathered from published sources — to model and perform new research about normal development and disease.

Since joining Cincinnati Children’s in 1986, I’ve enjoyed building tools and developing approaches that allow researchers to improve their understanding of (and find new treatments for) various medical conditions. In the Aronow lab, we aim to understand the molecular and cellular basis of normal organ and system development, physiology and disease. We use this knowledge to study diseases — and then prevent or cure them.

From an operational perspective, our work is based on team science. By computationally combining experimental and observational data with knowledge about molecular, cellular and biological systems, we produce data and ideas that translate to clinical practice.

For example, we’ve worked to predict new therapeutic approaches based on disease mechanisms for inflammatory bowel disease, eosinophilic esophagitis, sickle cell anemia, and neurological and psychiatric diseases.

Our team is working on efforts to define the transcriptome of the developing kidney, lung and brain. We are using stem cell-derived cells and organoids to dissect mechanisms that underlie organ development and function as well as oncogenesis. We’re also working on inferring novel disease indications for known drugs by semantically linking drug action and disease mechanism relationships.

One of my proudest career moments occurred in 2016 when I was named the John J. Hutton, MD, Chair for Biomedical Informatics at Cincinnati Children’s. In addition to holding this endowed chair, I also serve as co-director of the Computational Medicine Center.



Reconstructing differentiation networks and their regulation from time series single-cell expression data. Ding, J; Aronow, BJ; Kaminski, N; Kitzmiller, J; Whitsett, JA; Bar-Joseph, Z. PCR Methods and Applications. 2018.


Transcriptional risk scores link GWAS to eQTLs and predict complications in Crohn's disease. Marigorta, UM; Denson, LA; Hyams, JS; Mondal, K; Prince, J; Walters, TD; Griffiths, A; Noe, JD; Crandall, WV; Rosh, JR; et al. Nature Genetics. 2017; 49:1517-1521.


The complex genetics of hypoplastic left heart syndrome. Liu, X; Yagi, H; Saeed, S; Bais, AS; Gabriel, GC; Chen, Z; Peterson, KA; Li, Y; Schwartz, MC; Reynolds, WT; et al. Nature Genetics. 2017; 49:1152-1159.


Single-cell analysis of mixed-lineage states leading to a binary cell fate choice. Olsson, A; Venkatasubramanian, M; Chaudhri, VK; Aronow, BJ; Salomonis, N; Singh, H; Grimes, HL. Nature: New biology. 2016; 537:698-702.


Data mining differential clinical outcomes associated with drug regimens using adverse event reporting data. Sarangdhar, M; Tabar, S; Schmidt, C; Kushwaha, A; Shah, K; Dahlquist, JE; Jegga, AG; Aronow, BJ. Nature Biotechnology. 2016; 34:697-700.


Integrated Genomic Analysis of Diverse Induced Pluripotent Stem Cells from the Progenitor Cell Biology Consortium. Salomonis, N; Dexheimer, PJ; Omberg, L; Schroll, R; Bush, S; Huo, J; Schriml, L; Sui, SH; Keddache, M; Mayhew, C; et al. Stem Cell Reports. 2016; 7:110-125.

Ontology-guided segmentation and object identification for developmental mouse lung immunofluorescent images. Masci, AM; White, S; Neely, B; Ardini-Polaske, M; Hill, CB; Misra, RS; Aronow, B; Gaddis, N; Yang, L; Wert, SE; et al. BMC Bioinformatics. 2021; 22.

African Americans and European Americans exhibit distinct gene expression patterns across tissues and tumors associated with immunologic functions and environmental exposures. Singh, U; Hernandez, KM; Aronow, BJ; Wurtele, ES. Scientific Reports. 2021; 11.

Cancer Informatics for Cancer Centers: Scientific Drivers for Informatics, Data Science, and Care in Pediatric, Adolescent, and Young Adult Cancer. Kerlavage, AR; Kirchhoff, AC; Guidry Auvil, JM; Sharpless, NE; Davis, KL; Reilly, K; Reaman, G; Penberthy, L; Deapen, D; Hwang, A; et al. JCO Clinical Cancer Informatics. 2021; 5:881-896.

Identification of distinct tumor cell populations and key genetic mechanisms through single cell sequencing in hepatoblastoma. Bondoc, A; Glaser, K; Jin, K; Lake, C; Cairo, S; Geller, J; Tiao, G; Aronow, B. Communications Biology. 2021; 4.