Emergent dynamics in confluent tissues play an important role in many biological processes. Here, we study these dynamics through the lens of active matter physics, specifically focussing on two emergent phenomena: nematic collective behaviour in homeostasis and the dynamics of a growing tissue boundary.

We first examine the emergence of extensile nematic behaviour at the tissue level, and how a collection of contractile cells can give rise to it. By constructing and analysing a linearised hydrodynamic model, we show that this extensile behaviour results from fluctuating polar forces that arise from cell-substrate interactions. We show that polar fluctuations generically lead to extensile behaviour in the absence active contractile forces, and can still generate extensile behaviour in their presence. We then confirm our results by analysing the dynamics of nematic defects in a cell-based numerical model.

In order to analyse these nematic defects, one must have a reliable and efficient means of detecting them, which currently is not the case for many confluent tissues. Due to this, we then develop a machine learning model to detect nematic defects in confluent tissues that is readily implementable on experimental images of cell layers. We demonstrate that our model outperforms current detection techniques and that this manifests itself in our method requiring less data to accurately capture defect properties, improving the accuracy of experimental data interpretation.

Confluent tissue dynamics are not only important in homeostasis, but also during growth, such as in wound healing. As such, we also examine the dynamics of the boundary of a growing tissue. We study this problem using a novel lattice-Boltzmann method for a growing tissue with a moving front. We find that, at small system sizes, the interface fluctuations grow with scaling in agreement with the Kardar-Parisi-Zhang universality class. However, when using a density-dependent growth regime, we find the onset of a novel instability at larger system sizes, which we develop an analytical theory to characterise.

In this thesis we have developed new fundamental understanding of confluent tissue dynamics in homeostasis and the physics of growing tissue interface stability. We have also developed new defect detection methodology and simulation methods for modelling growing tissues. The tools and understanding generated here provide fruitful avenues of future research, and equip biophysicists to tackle further questions, in these important biological systems.