Fusion of single-cell transcriptome and DNA-binding data, for genomic network inference in cortical development.

ABSTRACT:

Background

Network models are well-established as very useful computational-statistical tools in cell biology. However, a genomic network model based only on gene expression data can, by definition, only infer gene co-expression networks. Hence, in order to infer gene regulatory patterns, it is necessary to also include data related to binding of regulatory factors to DNA.

Results

We propose a new dynamic genomic network model, for inferring patterns of genomic regulatory influence in dynamic processes such as development. Our model fuses experiment-specific gene expression data with publicly available DNA-binding data. The method we propose is computationally efficient, and can be applied to genome-wide data with tens of thousands of transcripts. Thus, our method is well su

SUBMITTER: Bartlett T 

PROVIDER: S-EPMC8176738 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature