DeltaNeTS+

DeltaNeTS+ infers direct gene targets from steady-state and time-series transcriptional profiles to elucidate molecular mechanisms of diseases and drug actions.

Key Features:

• Inference of Direct Gene Targets: Infers direct gene targets of drugs and diseases from steady-state and time-series transcriptional profiles, distinguishing direct perturbations from indirect effects within gene regulatory networks.
• Integration of Gene Regulatory Information: Leverages gene regulatory network models and structural network information to enhance prediction accuracy and reliability.
• Perturbation Scoring System: Generates per-gene perturbation scores whose magnitude reflects confidence and whose sign indicates induction (positive) or repression (negative).
• Application to Diverse Organisms and Cell Lines: Predicts gene targets in Caenorhabditis elegans and human cell lines such as T-cells and Calu-3.
• Analysis of Viral Infection Time Courses: Applied to time-course gene expression profiles from influenza A H1N1 and H5N1 infections to characterize dynamic cellular perturbations.

Scientific Applications:

• Disease pathogenesis and drug mechanism elucidation: Identifies direct transcriptional targets to dissect molecular mechanisms underlying diseases and drug actions.
• Drug target discovery and therapeutic prioritization: Supports discovery and prioritization of direct gene targets for drug development and targeted treatments.
• Temporal analysis of dynamic responses: Enables analysis of temporal gene expression changes in steady-state and time-course datasets to study dynamic cellular responses.

Methodology:

Employs network analysis grounded in gene regulatory models to infer direct transcriptional perturbations from steady-state and time-series expression profiles, integrates gene network structures across organisms, and outputs per-gene perturbation scores; designed to produce precise predictions with small sample sizes (~10s).