MIM

MIM calculates a Motif Independent Metric to quantify DNA sequence specificity in genome-wide mapping of protein–DNA interactions without relying on known transcription factor (TF) binding motifs.

Key Features:

• Motif Independent Metric: Provides a simple, systematic quantitative measure for assessing DNA sequence specificity independently of predefined TF binding motifs.
• Unbiased quantification: Offers an unbiased approach to evaluate sequence specificity across genomic regions.
• Data applicability: Applies to both simulated and real experimental DNA sequence data to detect sequence-specific interactions.
• Cell-type specificity analysis: Identifies cell-type-specific variation in sequence specificity, noting that H3K4me1 target sequences exhibit the highest specificity in embryonic stem (ES) cells.
• N-score model prediction: Utilizes the N-score model for target sequence prediction, demonstrating high accuracy for H3K4me1 targets in ES cells.

Scientific Applications:

• Genome function investigation: Maps protein–DNA interactions genome-wide to aid interpretation of regulatory roles of DNA sequences.
• Sequence-based prediction models: Provides a quantitative framework to develop models that predict sequence-specific interactions from DNA sequence features.
• Target sequence prediction: Enables prediction of target sequences such as H3K4me1 in ES cells using the N-score model with reported high accuracy.

Methodology:

Analyzes DNA sequence data to derive specificity metrics without depending on predefined motifs.