Algorithm for cellular reprogramming.

ABSTRACT: The day we understand the time evolution of subcellular events at a level of detail comparable to physical systems governed by Newton's laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology. With data-guided frameworks we can develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. Here we describe an approach for optimizing the use of transcription factors (TFs) in cellular reprogramming, based on a device commonly used in optimal control. We construct an approximate model for the natural evolution of a cell-cycle-synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points duri

SUBMITTER: Ronquist S 

PROVIDER: S-EPMC5692574 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature