cudaMMC

cudaMMC performs GPU-accelerated multiscale Simulated Annealing Monte Carlo sampling to model three-dimensional chromatin structures informed by 3C-based sequencing data such as ChiA-PET and Hi-C.

Key Features:

• GPU-Accelerated Computing: Leverages GPU parallel processing to accelerate computationally intensive steps relative to CPU-based implementations.
• Simulated Annealing Monte Carlo (SAMC): Uses a stochastic Simulated Annealing Monte Carlo algorithm to explore chromatin conformational space and identify low-energy configurations.
• Multiscale Modeling: Implements multiscale Monte Carlo approaches to generate chromatin models at varying resolutions and scales.
• Large-Model Ensemble Generation and Performance: Reduces computation time for generating ensembles of large chromatin models and demonstrates improved performance and stability on comparable workstations.

Scientific Applications:

• Chromatin 3D structure modeling: Generates ensembles of three-dimensional chromatin conformations for structural and spatial analyses.
• Interpretation of 3C-based sequencing data: Integrates contact information from ChiA-PET and Hi-C to constrain and inform 3D chromatin reconstruction.
• Transcriptional regulation studies: Facilitates investigation of how chromatin spatial organization relates to gene regulation and expression.

Methodology:

Integrates GPU acceleration with a multiscale Simulated Annealing Monte Carlo (SAMC) approach to stochastically sample chromatin conformational space and generate ensembles of 3D structures.