TFBSfinder

TFBSfinder identifies transcription factor binding sites by integrating a novel conservation metric, motif clustering, and position weight matrix inference to detect functional TFBS and synergistic TF pairs.

Key Features:

• Conservation Metric: Quantifies binding-site conservation across species to prioritize functionally conserved TFBS.
• Motif Clustering and Position Weight Matrices: Clusters DNA motifs and infers position weight matrices (PWMs) to represent transcription factor binding preferences.
• Performance on Benchmark Data: Demonstrates superior motif-identification performance in comparative analyses using synthetic data and yeast cell cycle transcription factors, recovering motifs that closely resemble known consensuses.

Scientific Applications:

• Yeast cell cycle regulation: Identifies individual cell cycle transcription factors and synergistic TF pairs to study gene regulation across cell-cycle phases, including predictions of 50 cell cycle TFs and 80 synergistic TF pairs.
• Regulatory network mapping: Integrates TFBS predictions with chromatin immunoprecipitation (ChIP) and microarray expression data to map regulatory interactions.
• Cross-species functional inference: Uses conservation-based assessment to infer functionally conserved TFBS across species.

Methodology:

The approach applies a conservation metric, motif clustering, and position weight matrix inference and leverages differential expression patterns across cell-cycle phases to predict individual TFs and synergistic TF pairs from chromatin immunoprecipitation (ChIP) and microarray data.