SeAMotE

SeAMotE (Sequence Analysis of Motifs Enrichment) identifies de novo regulatory sequence motifs in nucleic acid sequences to detect transcription and splicing factor binding sites and other protein–DNA and protein–RNA recognition patterns from large-scale high-throughput sequencing data.

Key Features:

• De novo motif discovery: Performs de novo discovery of sequence motifs in nucleic acid datasets.
• Motif search algorithm: Employs a motif search strategy based on pattern occurrences.
• Large-scale data handling: Analyzes large-scale sequence datasets and high-throughput sequencing data.
• Targeted recognition: Identifies motifs associated with transcription and splicing factor binding sites and protein–DNA and protein–RNA recognition.
• Benchmarking: Validated on 351 ChIP and 13 CLIP experiments with an average 80% accuracy in discovering discriminative motifs.

Scientific Applications:

• Transcription factor binding-site discovery: Identification of sequence motifs corresponding to transcription factor binding sites from ChIP datasets.
• Splicing factor motif identification: Detection of splicing factor binding motifs and protein–RNA recognition patterns from CLIP datasets.
• Regulatory element discovery in HTS data: Extraction of regulatory sequence patterns from large-scale high-throughput sequencing experiments.
• Method validation and benchmarking: Use in benchmarking discriminative motif discovery across ChIP and CLIP experiments.

Methodology:

Uses a motif search strategy based on pattern occurrences to perform de novo motif discovery.