Exploring In Complexity

My Research focus

Description of my research focus

My research focuses on pattern formation in biological systems. This kind of research emerges from a central question: Why do our biological systems know the pattern they should generate? For instance, why do bacteria choose to form clusters over homogeneous distribution? How do embryonal cells move collectively to differentiate various types of cells? Why don't they move chaotically? In these few years, scientists have built up various models to explain them. For example, the video on the right-hand side is the simulation of an active system. No attractive interaction between particles are applied. Interestingly, clusters are still formed in the system. Such a kind of phase transition is the so-called "Motility induce phase separation." I am interested in uncovering these unclarified physics in biological systems.

Recent Research Topic

These are my recent research topics

Embryo development

Embryo development

TBD

Previous Research Topic

These are my previous research topics

Traffic Model

Traffic Model

The physics of traffic systems has attracted interest from scientists since the 20th century since it provides a way to analyze active systems. Moreover, the analysis might shed light on the phase transition in active systems since, under some conditions, homogeneous free-flow traffic might turn out to be a traffic jam. In a traffic system, some traffic jams occur with an apparent source, such as a traffic accident, while some occur without any apparent reason. To understand such "phantom traffic jams," various models have been developed. In our research, we applied a classical car-following model, which Bando proposed in 1995, and introduced individual differences to illustrate human nature. Surprisingly, for a high-density traffic system, we analytically and numerically showed that jamming formation could be suppressed by the existence of individual differences. This suppression suggests that self-driving cars should take this factor into account.

Tumor Morphology

Tumor Morphology

Tumor morphology serves as an important prognostic indicator for transforming from benign to malignant tumors. Various models have been constructed to understand the mechanism of morphological instability on the surface of tumors. However, a linear growth rate is always employed to simplify the calculation. In contrast, empirical data have shown that the growth rate of tumors saturates in a nutrient-rich environment. By taking this factor into account, we construct a nutrient-regulated reaction-diffusion model to describe the evolution pattern of avascular tumors and the distribution of surrounding nutrients. Our model successfully reproduces the nutrient-deficiency-induced instability, which has been observed before. Moreover, our model predicts that a tumor should be stable in a nutrient-rich environment. Future clinical studies might be able to verify the existence of the newly discovered instability in tumor morphology.