GPUmotif

GPUmotif accelerates detection of transcription factor (TF) binding motifs in genomic sequences using GPU computation to enable efficient motif analysis for studying transcriptional regulation.

Key Features:

• GPU Acceleration: Utilizes NVIDIA CUDA to parallelize computations on GPUs and reduce computation time compared to CPU-based methods.
• Fragmentation Technique: Implements a fragmentation technique to minimize data transfer latency between different memory types and improve throughput.
• Energy Efficiency: Reduces energy consumption during large-scale motif analyses.
• Scalability and Accuracy: Builds upon the Hybrid Motif Sampler (HMS) algorithm and improves scalability and accuracy by eliminating the need to calculate matching probabilities position-by-position.

Scientific Applications:

• Transcription factor motif detection: Detects TF binding patterns in genomic sequences to investigate transcriptional regulation mechanisms.
• Protein–DNA interaction analysis: Analyzes large protein-DNA interaction datasets generated by advanced sequencing technologies.
• Model-based motif scanning: Supports model-based motif scanning workflows for targeted motif searches.
• De novo motif finding: Supports de novo motif discovery for identifying novel binding motifs from sequence data.

Methodology:

Uses NVIDIA CUDA-based GPU acceleration combined with a fragmentation technique to optimize data transfers between memory types and implements a variant of the Hybrid Motif Sampler (HMS) that removes position-by-position matching probability calculations.