Welcome to the JEFworks Lab

We are a bioinformatics research lab in the Center for Computational Biology and the Department of Biomedical Engineering at Johns Hopkins University. Meet our team!

Learn how you can join us!

We develop bioinformatics methods for analyzing spatially resolved sequencing and imaging data.

Spatial organization at both the subcellular-level within cells as well as the cellular-level within tissues play important roles in regulating cell identity and function. Recent technological advances have enabled high-throughput spatially resolved transcriptomic profiling at single-molecule and near-single-cell resolution. We develop machine learning and other statistical approaches as open-source computational software to take advantage of this new spatial information in deriving biological insights regarding how spatial organization plays a role in both healthy and diseased settings.

Overview of spatially resolved transcriptomics: imaging and capture-plus-sequencing technologies, and analyses including spatial pattern identification, joint spatial and gene expression clustering, pixel deconvolution, and cell-cell communication inference

We apply these bioinformatics methods to better understand the role of cellular heterogeneity in disease.

Illustration of tumor heterogeneity: interacting neoplastic subpopulations and non-neoplastic immune and stromal cells, tumor evolution across samples, and a single-cell gene expression heatmap

Advancements in high-throughput sequencing and imaging technologies have uncovered tremendous genetic, epigenetic, transcriptional, and spatial heterogeneity in various diseases but their impact on clinical outcomes is not well understood. We establish close collaborations with clinical collaborators to develop and apply bioinformatics methods that contribute to a more complete understanding of how cellular heterogeneity impacts disease progression and clinical prognosis.