TransModis

TransModis identifies direct transcription factor target genes by integrating sequence motif information, microarray gene expression profiles, and ChIP-chip data using a probabilistic model to reconstruct gene regulatory networks.

Key Features:

• Integration of multiple data types: Combines sequence motif information, microarray gene expression profiles, and ChIP-chip data for joint analysis.
• Probabilistic modeling: Uses a probabilistic framework to infer direct TF targets and reduce reliance on manual thresholding.
• Identification of immediate targets: Infers immediate/direct transcription factor target genes rather than indirect associations.
• Computational efficiency and robustness: Implements a computational approach reported to be efficient and robust for genome-scale analyses.

Scientific Applications:

• Transcription factor perturbation validation: Validated using TF perturbation experiments involving Pho4p in Saccharomyces cerevisiae to predict TF targets.
• Genome-wide comparative analysis: Compared genome-wide in S. cerevisiae with two other methods to assess performance.
• Aging and DAF-16 targets in C. elegans: Applied to identify 189 genes tightly regulated by DAF-16 in Caenorhabditis elegans and to reveal differential motif preference when DAF-16 acts as an activator or repressor.

Methodology:

TransModis employs a probabilistic framework that integrates sequence motifs, microarray gene expression data, and ChIP-chip results to infer direct transcription factor targets.