Project in Prairie
Laura Cantini will develop computational methods for multi-modal single-cell data integration. She will in particular combine multi-omics joint dimensionality reduction, to identify the cell types and states present in a biological sample, and network-based methods to reconstruct the multi-omics regulatory mechanisms underlying each cell type/state. Finally, by applying the developed approaches to patient-derived data, she will contribute to improve our understanding of cancer heterogeneity and its underlying molecular mechanisms.
The timely detection and successful treatment of cancer depends on our ability to understand when, why, and how a subpopulation of cells deviates away from a healthy state or acquires drug resistance. Single-cell multi-modal data, produced at increasing peace, offer the opportunity to tackle these questions. The current major bottleneck is the crucial need for computational methods able to translate this wealth of information into actionable biological knowledge.

