NETISCE: a network-based tool for cell fate reprogramming.

ABSTRACT: The search for effective therapeutic targets in fields like regenerative medicine and cancer research has generated interest in cell fate reprogramming. This cellular reprogramming paradigm can drive cells to a desired target state from any initial state. However, methods for identifying reprogramming targets remain limited for biological systems that lack large sets of experimental data or a dynamical characterization. We present NETISCE, a novel computational tool for identifying cell fate reprogramming targets in static networks. In combination with machine learning algorithms, NETISCE estimates the attractor landscape and predicts reprogramming targets using signal flow analysis and feedback vertex set control, respectively. Through validations in studies of cell fate reprogramming fro

SUBMITTER: Marazzi L 

PROVIDER: S-EPMC9209484 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature