The bottom-up approach to defining life: deciphering the functional organization of biological cells via multi-objective representation of biological complexity from molecules to cells.

In silico representation of cellular systems needs to represent the adaptive dynamics of biological cells, recognizing a cell's multi-objective topology formed by temporally cohesive intracellular structures. The design of these models needs to address the hierarchical and concurrent nature of cellular functions and incorporate the ability to self-organize in response to transitions between healthy and pathological phases, and adapt accordingly. The functions of biological systems are constantly progressing, due to the ever changing demands of their environment. Biological systems meet these demands by pursuing objectives, aided by their constituents, giving rise to biological functions. A biological cell is organized into an objective/task hierarchy. These objective hierarchy corresponds to the nested nature of temporally cohesive structures and representing them will facilitate in studying pleiotropy and polygeny by modeling causalities propagating across multiple interconnected intracellular processes. Although biological adaptations occur in physiological, developmental and reproductive timescales, the paper is focused on adaptations that occur within physiological timescales, where the biomolecular activities contributing to functional organization, play a key role in cellular physiology. The paper proposes a multi-scale and multi-objective modeling approach from the bottom-up by representing temporally cohesive structures for multi-tasking of intracellular processes. Further the paper characterizes the properties and constraints that are consequential to the adaptive dynamics in biological cells.