GRAND

GRAND provides genome-scale gene regulatory network models across human tissues, cancers, cell lines, and small-molecule perturbations to enable comparative analysis of transcription factor, microRNA, and gene regulatory interactions.

Key Features:

• Extensive Network Collection: Contains 12,468 genome-scale gene regulatory networks representing 36 human tissues, 28 cancer types, and 1,378 unperturbed cell lines.
• Molecular Interaction Scope: Models interactions among transcription factors (TFs), microRNAs (miRNAs), and their target genes across diverse biological conditions.
• Small-Molecule Perturbation Scores: Includes 173,013 TF and gene targeting scores associated with 2,858 small-molecule-induced perturbations in cell lines, linked to phenotypic information.
• Disease–Drug Matching by Network Properties: Enables matching of disease regulatory states to candidate small molecules based on alterations in regulatory network properties.

Scientific Applications:

• Comparative network analysis: Compare structural and regulatory differences between normal and diseased tissues at the TF, miRNA, and gene levels.
• Drug effect prediction and repurposing: Predict effects of small molecules on TF and gene targeting profiles to support drug discovery and repurposing efforts.
• Perturbation response analysis: Assess how small-molecule perturbations alter regulatory networks and associated phenotypes in cell lines.
• Tissue identity and function studies: Investigate regulatory mechanisms underlying tissue-specific identity and function using genome-scale networks.

Methodology:

Networks were constructed by modeling interactions between transcription factors, microRNAs, and target genes derived from high-throughput experimental data and computational predictions.