Boolean Feedforward Neural Network Modeling of Molecular Regulatory Networks for Cellular State Conversion.

ABSTRACT: The molecular regulatory network (MRN) within a cell determines cellular states and transitions between them. Thus, modeling of MRNs is crucial, but this usually requires extensive analysis of time-series measurements, which is extremely difficult to obtain from biological experiments. However, single-cell measurement data such as single-cell RNA-sequencing databases have recently provided a new insight into resolving this problem by ordering thousands of cells in pseudo-time according to their differential gene expressions. Neural network modeling can be employed by using temporal data as learning data. In contrast, Boolean network modeling of MRNs has a growing interest, as it is a parameter-free logical modeling and thereby robust to noisy data while still capturing essential dynamics o

SUBMITTER: Choo SM 

PROVIDER: S-EPMC7736109 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature