Bridging biological scales by state-space analysis and modeling using molecular, tissue cytometric and physiological data

Abstract

Combining data streams across different levels of biological organization such as molecular, cellular, and physiological responses support to a system-wide view in biology. Recently, an unbiased analysis of tissues that provides data-rich descriptors of tissue architecture, cell types, and cell states has become available. As tissues are centrally located in the biological hierarchy, these advancements give rise to a new class of state variables that are critical to elucidate both underlying cellular, molecular and emergent physiological properties. Concepts to statistically identify, correlate, and model relationships across scales are introduced, which rely on a state-space matrix derived by multi-omics data aggregation.