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ColabFold: making protein folding accessible to all
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mirdita, Milot | - |
dc.contributor.author | Schutze, Konstantin | - |
dc.contributor.author | Moriwaki, Yoshitaka | - |
dc.contributor.author | Heo, Lim | - |
dc.contributor.author | Ovchinnikov, Sergey | - |
dc.contributor.author | Steinegger, Martin | - |
dc.date.accessioned | 2022-09-30T06:04:57Z | - |
dc.date.available | 2022-09-30T06:04:57Z | - |
dc.date.created | 2022-06-27 | - |
dc.date.created | 2022-06-27 | - |
dc.date.created | 2022-06-27 | - |
dc.date.issued | 2022-06 | - |
dc.identifier.citation | Nature Methods, Vol.19 No.6, pp.679-682 | - |
dc.identifier.issn | 1548-7091 | - |
dc.identifier.uri | https://hdl.handle.net/10371/185150 | - |
dc.description.abstract | ColabFold offers accelerated prediction of protein structures and complexes by combining the fast homology search of MMseqs2 with AlphaFold2 or RoseTTAFold. ColabFold's 40-60-fold faster search and optimized model utilization enables prediction of close to 1,000 structures per day on a server with one graphics processing unit. Coupled with Google Colaboratory, ColabFold becomes a free and accessible platform for protein folding. ColabFold is open-source software available at https://github.cpm/sokrypton/colabfold and its novel environmental databases are available at https://colab-fold.mmseqs.com. | - |
dc.language | 영어 | - |
dc.publisher | Nature Publishing Group | - |
dc.title | ColabFold: making protein folding accessible to all | - |
dc.type | Article | - |
dc.identifier.doi | 10.1038/s41592-022-01488-1 | - |
dc.citation.journaltitle | Nature Methods | - |
dc.identifier.wosid | 000802918900005 | - |
dc.identifier.scopusid | 2-s2.0-85131047515 | - |
dc.citation.endpage | 682 | - |
dc.citation.number | 6 | - |
dc.citation.startpage | 679 | - |
dc.citation.volume | 19 | - |
dc.description.isOpenAccess | Y | - |
dc.contributor.affiliatedAuthor | Steinegger, Martin | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.subject.keywordPlus | PREDICTION | - |
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