BioinformaticsBioinformaticsPeer-reviewed journal article
cudaMMC - GPU-enhanced Multiscale Monte Carlo Chromatin 3D Modelling
Michał WlasnowolskiiD, Pawel Grabowski, Damian Roszczyk, Krzysztof KaczmarskiiD, Dariusz PlewczyńskiiD
Abstract
MotivationInvestigating the 3D structure of chromatin provides new insights into transcriptional regulation. With the advancements in 3C new-sequencing techniques such as ChiA-PET and Hi-C, there has been a substantial increase in the volume of collected data, necessitating faster algorithms for chromatin spatial modelling. This study presents the cudaMMC method, which utilises the Simulated Annealing Monte Carlo approach extended by GPU-accelerated computing to generate ensembles of chromatin 3D structures efficiently. ResultsThe cudaMMC calculations demonstrate significantly faster performance and lower (better) model scores compared to our previous method on the same workstation. cudaMMC substantially reduces the computation time required for generating ensembles of large chromatin models, making it an invaluable tool for studying chromatin spatial conformation. AvailabilityOpen-source software and manual and sample data are freely available on https://github.com/SFGLab/cudaMMC ContactDariusz.Plewczynski@pw.edu.pl
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- 3
- FWCI
- 0.27
- Field percentile
- 44th percentile
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