# Computational insights in cell physiology

## TL;DR

The paper discusses how computational models help understand complex cellular processes and their regulation.

## Contribution

The paper presents selected examples showing how modeling addresses complex questions in cellular physiology.

## Key findings

- Modeling aids in understanding rhythmic phenomena and signaling in cells.
- Computational approaches reveal insights into cell differentiation and metabolic regulation.
- Examples include chronopharmacology and calcium dynamics.

## Abstract

Physiological processes are governed by intricate networks of transcriptional and post-translational regulations. Inter-cellular interactions and signaling pathways further modulate the response of the cells to environmental conditions. Understanding the dynamics of these systems in healthy conditions and their alterations in pathologic situations requires a “systems” approach. Computational models allow to formalize and to simulate the dynamics of complex networks. Here, we briefly illustrate, through a few selected examples, how modeling helps to answer non-trivial questions regarding rhythmic phenomena, signaling and decision-making in cellular systems. These examples relate to cell differentiation, metabolic regulation, chronopharmacology and calcium dynamics.