University of Colorado Anschutz Medical Campus
The Zhang Lab develops computational machine learning and AI methods for single-cell omics to study inflammatory disease for translational medicine in the University of Colorado Anschutz Medical Campus. The lab is supported by multiple NIH and foundation grants, including NIH NIAMS R01, the NIH AMP-AIM Team Science Leadership Scholars Program, the NIH Office of Women's Health, as well as the Arthritis Foundation, Arthritis National Research Foundation, and PhRMA.
| scLASER | A robust framework for simulating and detecting time-dependent single-cell dynamics in longitudinal studies. |
| CellPhenoX | An explainable machine learning method for identifying cell phenotypes to predict clinical outcomes from single-cell multi-omics data. 📦 Available on PyPI: pyCellPhenoX |
| STEAM | Spatial Transcriptomics Evaluation Algorithm and Metric for benchmarking clustering performance. |
| STew | A Spatial Transcriptomic multi-viEW representation learning method that jointly characterizes gene expression variation and spatial information in a shared, scalable low-dimensional space. |
| Longitudinal_preRA | Analytic code for the StopRA mechanistic study, including data integration and disease progression modeling using CITE-seq, mass cytometry, scASAP-seq, TCR/BCR-seq, and more. |
| MultiScale_ComplementMacrophage | Analytic code for complement-focused single-cell meta-analysis, complement-treated macrophage-fibroblast co-culture analysis, and a novel spatial neighborhood-based modeling for gene-level associations for spatial transcriptomics |
