Identification via Numerical Computation of Transcriptional Determinants of a Cell Phenotype Decision Making.

ABSTRACT: Complex cellular processes, such as phenotype decision making, are exceedingly difficult to analyze experimentally, due to the multiple-layer regulation of gene expression and the intercellular variability referred to as biological noise. Moreover, the heterogeneous experimental approaches used to investigate distinct macromolecular species, and their intrinsic differential time-scale dynamics, add further intricacy to the general picture of the physiological phenomenon. In this respect, a computational representation of the cellular functions of interest can be used to extract relevant information, being able to highlight meaningful active markers within the plethora of actors forming an active molecular network. The multiscale power of such an approach can also provide meaningful descrip

SUBMITTER: Cortesi M 

PROVIDER: S-EPMC6598594 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature