Rosemary Braun Computational biology at multiple scales

Research Interests

Living systems are governed by a complex network of molecular interactions involving hundreds of thousands of interacting elements. These systems are finely tuned to produce precise biological effects, robust enough to tolerate intrinsic and extrinsic variability, and flexible enough to adapt to environmental changes. 

Our computational biology lab works at the interface between mathematics and the life sciences to advance our understanding of how macroscopic phenotypes emerge from the complex interplay of microscopic interactions. We develop powerful statistical and computational methods to model living systems at multiple scales — from the atomic level, to the gene level, to the systems level, to the tissue/organismal level, and finally to the population level — and apply these methods in close collaboration with experimentalists and clinicians.  Our research falls into three major areas:
  • Deducing the "Rules of Life": reverse-engineering the structure of regulatory networks from high-throughput data, and using simulations to understand how changes in molecular interactions generate observable phenotypes
  • Network Systems Biology: leveraging the power of graph theory and computational statistics to analyze *omic data in the context of known networks and understand how these networks can yield behaviors that are more than the sum of their parts
  • Temporal Organization of Living Systems: developing machine learning algorithms to predict dynamics, and using dynamical systems theory to elucidate the role of cellular timekeeping in coordinating physiological processes. 

Selected Publications

GeneSurrounder: network-based identification of disease genes in expression data. Shah SD and Braun R. BMC Bioinformatics. 2019 May 6;20:229.

Mutation, drift and selection in single-driver hematologic malignancy: Example of secondary myelodysplastic syndrome following treatment of inherited neutropenia. Wojdyla T, Mehta H, Glaubach T, Bertolusso R, Iwanaszko M, Braun R, Corey SJ, and Kimmel M. PLoS Computational Biology. 2019 January 7;15(1):e1006664.

Time-lagged Ordered Lasso for network inference. Nguyen P and Braun R. BMC Bioinformatics. 2018 December 29;19:545.

regQTLs: Single nucleotide polymorphisms that modulate microRNA regulation of gene expression in tumors. Wilk G and Braun R. PLoS Genetics. 2018 December 17;14(12):e1007837.

Universal method for robust detection of circadian state from gene expression. Braun R, Kath WL, Iwanaszko M, Kula-Eversole E, Abbott SM, Reid KJ, Zee PC, and Allada R. PNAS. 2018 September 25;115(39):E9247-E9256.

View all publications by Rosemary Braun listed in the National Library of Medicine (PubMed).