Towards the Modelling of Phase Transitions in Biological Systems using Physiology Space and Thermodynamic Approaches


PhysioSpace (Lenz et. al. 2013) extracts physiologically relevant signatures from reference data set (usually a compendium of public data sets) by integrating and transforming heterogeneous reference gene expression data into a set of physiology specific patterns, called PhysioSpace. New experimental data can be mapped to these PhysioSpaces, resulting in ”similarity” scores providing quantitative similarity of new experiment to an a priori compendium.
In this project we aim to develop and expand PhysioSpace as a mean to study phase transition in the context of life sciences. PhysioSpace will be adapted to work as a bridge between phase transition concepts in thermodynamics and biological data, enabling the prediction of phase transitions in biological systems.

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