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Dataset Information

Identification of transcription factors potentially involved in human adipogenesis in vitro.


ABSTRACT:

Background

Increased adiposity in humans leads to obesity, which is a major risk factor for cardiovascular disease, type 2 diabetes, and cancer. We previously conducted an extensive unbiased in vitro transcriptomic analysis of adipogenesis, using human adipose-derived stromal cells (ASCs). Here, we have applied computational methods to these data to identify transcription factors (TFs) that constitute the upstream gene regulatory networks potentially, driving adipocyte formation in human ASCs.

Methods

We used Affymetrix Transcription Analysis Console™ v3.0 for calculating differentially expressed genes. MATCH™ and F-MATCH™ algorithms for TF identification. STRING v10 to predict protein-protein interactions between TFs.

Results

A number of TFs that were reported to hav

SUBMITTER: Ambele MA 

PROVIDER: S-EPMC5441431 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature