Identifying temporal trace of biological process during phase transition

Abstract

Phase transition widely exists in the biological world, such as the transformation of cell cycle phases, cell differentiation stages, cancer development steps, and so on. These are considered as the conversions of a genetic system from one phenotype/genotype to another. In previous studies, the molecular mechanisms of biological phase transition have attracted much attention, in particular, on the different genotypes related to specific phase but less of focus on the cascade of genes' functions during the phase change. However, it is a fundamental but important mission to track the temporal characteristics of a genetic system during specific phase transition or process, which can offer clues for understanding life and advancing its quality. By overcoming the hurdles of traditional time segmentation and temporal biclustering methods, a causal process model (CPM) in the present work is proposed to study the biological phase transition in a systematic way: boundary gene estimation for gene-specific segmentation and temporal block construction for whole data division. After the computational validation on synthetic data, CPM was used to analyze the well-known Yeast cell cycle data to identify the time periods of six phases in two cell cycles, and revealed phase/cycle related biological processes. These primary results demonstrate that CPM is efficient comparing to traditional methods, and has potential to elucidate the genetic mechanism with more complicated phase transitions.