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Bridging biological scales by state–space analysis and modeling using molecular, tissue cytometric and physiological data
Author(s) -
Kriete Andres
Publication year - 2006
Publication title -
cytometry part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.316
H-Index - 90
eISSN - 1552-4930
pISSN - 1552-4922
DOI - 10.1002/cyto.a.20226
Subject(s) - hierarchy , computational biology , biological data , bridging (networking) , computer science , biology , biological system , bioinformatics , computer network , economics , market economy
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. © 2006 International Society for Analytical Cytology.