Differences in the collective behaviour of the genes in the cancerous and normal cell from the perspective of inverse statistical physics

Abstract

Cancer is commonly known as a disease of the genes. Almost all the studies about cancers are based on finding the effective genes for each cancer and most of the efforts for diagnosing or curing cancer have faced several challenges. From the point of view of complexity, collective behaviors that have emerged from the interactions of many-body systems are not solely describable by knowing about the system’s building blocks (genes) and we cannot understand what happens at a higher level of organization by just knowing how each element works at a lower scale! We know, each gene’s expression affects other genes expression levels and this correlation causes a collective behavior which that alters the expression levels of the genes. In this study, instead of following the common reductionist view, we use the techniques of inverse statistical physics and infer the interaction matrix of the genes. Then, by applying the balance theory, we show the differences between the social behavior of cancer genes and normal genes as a whole. Our results show that the energy distribution of triads formed in the interaction networks behaves in a power-law manner and the energy of the normal network is higher than the cancer network.

Keywords

• cancer
• inverse statistical physics
• inference problem
• complex networks
• gene regulatory network
• balance theory