Presentation
Scalable Genomic Context Analysis with GCsnap2 on HPC Clusters
Presenter
DescriptionGCsnap2 Cluster is a scalable, Python-based high performance solution for genomic context analysis, co-developed by computer and life scientists to overcome the scalability limitations of its predecessor, GCsnap1 Desktop. Leveraging distributed computing with mpi4py.futures, GCsnap2 Cluster achieved a 30× improvement in execution time, and can now perform genomic context analyses of hundreds of thousands of protein-coding gene sequences on HPC clusters. Its modular architecture enables creation of task-specific workflows and flexible deployment on various computational environments, making it ideally-suited for bioinformatics studies of large-scale datasets. This work highlights the potential of applying similar approaches to solve scalability challenges in other scientific domains that rely on large-scale data analysis pipelines.
TimeTuesday, June 1719:00 - 21:00 CEST
LocationCampussaal - Plenary Room
SessionPoster Session and Reception
Event Type
PASC Poster
Authors
