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DTSTAMP:20250822T115805Z
LOCATION:Campussaal - Plenary Room
DTSTART;TZID=Europe/Stockholm:20250617T103000
DTEND;TZID=Europe/Stockholm:20250617T110000
UID:submissions.pasc-conference.org_PASC25_sess150_pos147@linklings.com
SUMMARY:P38 - Scalable Genomic Context Analysis with GCsnap2 on HPC Cluste
 rs
DESCRIPTION:Reto Krummenacher and Osman Seckin Simsek (University of Basel
 ); Michèle Leemann, Leila T. Alexander, and Torsten Schwede (University of
  Basel, Swiss Institute of Bioinformatics); Florina M. Ciorba (University 
 of Basel); and Joana Pereira (University of Basel, Swiss Institute of Bioi
 nformatics)\n\nGCsnap2 Cluster is a scalable, Python-based high performanc
 e solution for genomic context analysis, co-developed by computer and life
  scientists to overcome the scalability limitations of its predecessor, GC
 snap1 Desktop. Leveraging distributed computing with mpi4py.futures, GCsna
 p2 Cluster achieved a 30× improvement in execution time, and can now perfo
 rm genomic context analyses of hundreds of thousands of protein-coding gen
 e sequences on HPC clusters. Its modular architecture enables creation of 
 task-specific workflows and flexible deployment on various computational e
 nvironments, making it ideally-suited for bioinformatics studies of large-
 scale datasets. This work highlights the potential of applying similar app
 roaches to solve scalability challenges in other scientific domains that r
 ely on large-scale data analysis pipelines.\n\nSession Chair: David Moxey 
 (King's College London)\n\n
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