New understanding of transcriptional control is gained by examining the 3D structure of chromatin. The development of 3C next-generation sequencing technologies like ChiA-PET and Hi-C has brought to light the necessity for more effective chromatin spatial modelling algorithms due to the explosion in data volume. In order to quickly create ensembles of 3D chromatin structures, this paper introduces the cudaMMC method, which is based on the Simulated Annealing Monte Carlo approach and improved by GPU-accelerated computing.
On https://github.com/SFGLab/cudaMMC, open-source software, a documentation, and sample data are all freely available.