SINCERITIES: inferring gene regulatory networks from time-stamped single cell transcriptional expression profiles.

ABSTRACT:

Motivation

Single cell transcriptional profiling opens up a new avenue in studying the functional role of cell-to-cell variability in physiological processes. The analysis of single cell expression profiles creates new challenges due to the distributive nature of the data and the stochastic dynamics of gene transcription process. The reconstruction of gene regulatory networks (GRNs) using single cell transcriptional profiles is particularly challenging, especially when directed gene-gene relationships are desired.

Results

We developed SINCERITIES (SINgle CEll Regularized Inference using TIme-stamped Expression profileS) for the inference of GRNs from single cell transcriptional profiles. We focused on time-stamped cross-sectional expression data, commonly generated from tran

SUBMITTER: Papili Gao N 

PROVIDER: S-EPMC5860204 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature