GPU-accelerated homology search with MMseqs2
| dc.contributor.author | Kallenborn, Felix | |
| dc.contributor.author | Chacon, Alejandro | |
| dc.contributor.author | Hundt, Christian | |
| dc.contributor.author | Sirelkhatim, Hassan | |
| dc.contributor.author | Didi, Kieran | |
| dc.contributor.author | Cha, Sooyoung | |
| dc.contributor.author | Dallago, Christian | |
| dc.contributor.author | Mirdita, Milot | |
| dc.contributor.author | Schmidt, Bertil | |
| dc.contributor.author | Steinegger, Martin | |
| dc.date.accessioned | 2026-07-23T11:55:01Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Rapidly growing protein databases demand faster sensitive search tools. Here the graphics processing unit (GPU)-accelerated MMseqs2 delivers 6× faster single-protein searches than CPU methods on 2 × 64 cores, speeds previously requiring large protein batches. For larger query batches, it is the most cost-effective solution, outperforming the fastest alternative method by 2.4-fold with eight GPUs. It accelerates protein structure prediction with ColabFold 31.8× over the standard AlphaFold2 pipeline and protein structure search with Foldseek by 4–27×. | en_GB |
| dc.identifier.doi | https://doi.org/10.25358/openscience-15912 | |
| dc.identifier.uri | https://openscience.ub.uni-mainz.de/handle/20.500.12030/15933 | |
| dc.language.iso | eng | |
| dc.rights | CC-BY-4.0 | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject.ddc | 004 Informatik | de_DE |
| dc.subject.ddc | 004 Data processing | en_GB |
| dc.title | GPU-accelerated homology search with MMseqs2 | |
| dc.type | Zeitschriftenaufsatz | de_DE |
| jgu.apc.netprice | 0,00 | |
| jgu.apc.price | 0,00 | |
| jgu.apc.taxrate | 0 | |
| jgu.apc.transformationcontract | Nature | |
| jgu.dfg.year | 2025 | |
| jgu.identifier.uuid | bdf409d3-d2e6-40e7-9dda-299d05c08e80 | |
| jgu.journal.title | Nature methods : techniques for life scientists and chemists | |
| jgu.journal.volume | 22 | |
| jgu.nationalcurrency.eur | 0,00 | |
| jgu.organisation.department | FB 08 Physik, Mathematik u. Informatik | de_DE |
| jgu.organisation.name | Johannes Gutenberg-Universität Mainz | de_DE |
| jgu.organisation.number | 7940 | |
| jgu.organisation.place | Mainz | |
| jgu.organisation.ror | https://ror.org/023b0x485 | |
| jgu.pages.end | 2027 | |
| jgu.pages.start | 2024 | |
| jgu.publisher.doi | 10.1038/s41592-025-02819-8 | |
| jgu.publisher.eissn | 1548-7105 | |
| jgu.publisher.name | Nature | |
| jgu.publisher.place | London | |
| jgu.publisher.year | 2025 | |
| jgu.rights.accessrights | openAccess | en_GB |
| jgu.subject.ddccode | 004 | |
| jgu.subject.dfg | Ingenieurwissenschaften | de_DE |
| jgu.type.contenttype | Other | en_GB |
| jgu.type.dinitype | Article | en_GB |
| jgu.type.resource | Text | en_GB |
| jgu.type.version | Published version | en_GB |
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