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Memory-efficient, accelerated protein interaction inference with blocked, multi-GPU D-SCRIPT

delete2025-10-01
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PRE
AI
D
Daniel E. Schäffer
S
Samuel Sledzieski
L
Lenore Cowen *
B
Bonnie Berger *
DOI:10.1093/bioinformatics/btaf564delete
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Abstract

Abstract

En 中文
D-SCRIPT is a powerful tool for high-throughput inference of protein-protein interactions (PPIs), but it is expensive in time and memory to infer all PPIs for network-/proteome-level analyses. We introduce D-SCRIPT with blocked multi-GPU parallel inference, which substantially reduces memory usage across tasks and computational systems (13.8x for a representative large proteome) and enables multi-GPU parallelism.Availability and implementation Blocked multi-GPU parallel inference has been integrated into the main D-SCRIPT package, available at https://github.com/samsledje/D-SCRIPT. An archived version of the code at time of submission can be found at https://doi.org/10.5281/zenodo.16325182.

Journal

Bioinformatics cover
Bioinformatics
IF:
5.4
Papers:
1.1K
Citations:
17.9W

Organization

F
flatiron institute
Scholars:
207
Papers: 163
Citations: 0
S
Simons Foundation
Scholars:
200
Papers: 135
Citations: 1.1K