ArticleBioinformatics (Oxford, England)2023
cudaMMC: GPU-enhanced multiscale Monte Carlo chromatin 3D modelling.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- enhancer3D: 3D chromatin structures and enhancer-promoter distance profiles for archaic and modern human genomes.Nucleic acids research · 2026Article
- Multiscale molecular modeling of chromatin with MultiMM: From nucleosomes to the whole genome.Computational and structural biotechnology journal · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
motivationInvestigating the 3D structure of chromatin provides new insights into transcriptional regulation. With the evolution of 3C next-generation sequencing methods like ChiA-PET and Hi-C, the surge in data volume has highlighted the need for more efficient chromatin spatial modelling algorithms. This study introduces the cudaMMC method, based on the Simulated Annealing Monte Carlo approach and enhanced by GPU-accelerated computing, to efficiently generate ensembles of chromatin 3D structures.
resultsThe cudaMMC calculations demonstrate significantly faster performance with better stability compared to our previous method on the same workstation. cudaMMC also substantially reduces the computation time required for generating ensembles of large chromatin models, making it an invaluable tool for studying chromatin spatial conformation. AVAILABILITY AND IMPLEMENTATION: Open-source software and manual and sample data are freely available on https://github.com/SFGLab/cudaMMC.
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