Biomedical Informatics

Faculty Labs

The Andorf Lab primarily focuses on computational approaches in the intersection of immunological and clinical research to study underlying causes and novel approaches for the prevention, diagnosis and treatment of disease.

The Aronow Lab advances genomic medicine through collaborative, translational bioinformatics research, developing innovative algorithms, tools, and informatics systems that integrate diverse data and disciplines to generate high‑impact biomedical insights.

Our research focuses on utilizing and integrating large-scale molecular, clinical and phenotypic data to understand connections between genotypes and phenotypes for human diseases, such as premature birth and genetic disorders associated with congenital heart defects.

The Decision Support Analytics Workgroup (DSAW) at Cincinnati Children’s Hospital is a collaborative community of clinical informaticists, researchers, and healthcare professionals dedicated to designing and advancing effective, efficient, and user-centered pediatric clinical decision support.

The Jegga Lab develops data-driven systems biology approaches to translate genomics and biomedical big data into actionable insights for understanding disease mechanisms and accelerating drug discovery, particularly for rare disorders.

Our lab develops and applies computational methods in structural bioinformatics, computational genomics, and systems biology to mine and analyze biomedical data, with a focus on predicting protein interactions, assessing model quality, and creating widely used bioinformatics tools for protein and complex annotation.

The Miraldi lab’s focus is mathematical modeling of the immune system from high-dimensional genomics measurements.

The Pestian lab uses advanced artificial intelligence and computational methods to integrate clinical, biological, environmental, and linguistic data in order to understand emotions, enable early identification, and improve treatment of neuropsychiatric illnesses, particularly in children and adolescents.

The Roskin Lab integrates computational, bioinformatic, and molecular biology approaches to analyze high-dimensional immunological data and understand how adaptive immune receptor repertoires change in human disease and antigen exposure.

The Salomonis Lab develops AI‑driven computational and multi‑omic approaches to understand disease‑associated splicing dysregulation and to identify broadly reusable immune modulatory therapies targeting mis‑splicing across cancer and genetic disease.

Our lab uses computational approaches to uncover how genes are turned on and off, revealing the regulatory mechanisms that drive human traits and disease.

Our lab uses bioinformatics, multi-omics, and single-cell analysis to map lung development and disease, uncover regulatory mechanisms, and identify origins and therapeutic targets for disorders like LAM.