REDUCE

REDUCE applies motif-based regression to microarray expression data and regulatory DNA sequences to identify oligonucleotide transcription factor binding sites and correlate motif presence with mRNA expression to infer transcriptional module activity.

Key Features:

• Input Requirements: Requires genome-wide absolute or relative mRNA abundances from microarrays and the DNA sequences of regulatory regions associated with each probed gene.
• Motif Detection: Detects oligonucleotide motifs within regulatory regions using unbiased statistical methods that correlate motif presence with mRNA expression levels.
• Regression Analysis: Applies motif-based regression analysis to infer the activity of transcriptional modules linked to identified motifs.
• Supported Organisms: Supports genome-wide analyses in yeast, worm, and fly.

Scientific Applications:

• Transcription factor binding site identification: Identifies TFBS by linking oligonucleotide motifs in regulatory DNA to microarray-derived mRNA expression patterns.
• Gene regulatory network inference: Infers activity of transcriptional modules and aids reconstruction of gene regulatory networks.
• Functional genomics and systems biology: Connects motif occurrence to expression phenotypes to support functional-genomics and systems-biology studies.

Methodology:

Uses unbiased statistical detection of oligonucleotide motifs in regulatory regions and motif-based regression applied to microarray mRNA abundances to infer transcriptional module activity.