Uncovering Functional Gene Regulatory Networks in Bulk and Single-Cell Data through Robust Transcription Factor Activity Estimation and Model-Guided Experimental Validation

This dataset contains input files and output gene regulatory networks (GRNs) inferred using multiple algorithms and transcription factor activity (TFA) estimation strategies. GRNs were computed from expression data from three biological contexts: Saccharomyces cerevisiae (yeast) bulk transcriptomes, mammalian bulk transcriptomes, and single-cell RNA-seq (scRNA-seq) datasets. Algorithms were applied with different TFA configurations (e.g., NCA TFA, regularized TFA, algorithm-inbuilt TFA estimators). Data are organized into either file_inputs or file_output directories: file_inputs/ – expression matrices, prior networks, regulator lists, TFA estimates file_outputs/ – inferred GRNs, structured by dataset, method, and TFA configuration For further file information, see documentation provided in README.md file included in the data record.