T-Gene

T-Gene predicts target genes regulated by transcription factors by integrating histone modification/expression correlations with genomic distance to identify TF binding sites linked to gene promoters.

Key Features:

• Comprehensive Prediction Model: T-Gene integrates histone modification/expression correlation and genomic distance into a combined scoring system to predict which genes are regulated by a given transcription factor and the specific binding sites involved.
• High Predictive Accuracy: The algorithm achieves a median positive predictive value (PPV) above 50% when predicting regulatory elements bound by a TF that contact a gene's promoter.
• Robustness with Limited Data: T-Gene maintains a median PPV above 40% when extensive histone and expression datasets are unavailable by relying on genomic distance metrics alone.
• Statistical Significance Estimation: Each prediction includes an estimate of statistical significance.

Scientific Applications:

• Functional Genomics: Mapping transcription factor (TF) regulatory networks to link TF binding sites with target gene expression.
• Disease Research: Identifying dysregulated target genes and regulatory elements in conditions with altered TF activity.
• Evolutionary Biology: Studying conservation of regulatory elements and TF-target interactions across species.

Methodology:

T-Gene computes a combined score by integrating histone modification/expression correlations with genomic distance to predict regulatory interactions.