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For: de Crécy-lagard V, Amorin de Hegedus R, Arighi C, Babor J, Bateman A, Blaby I, Blaby-haas C, Bridge AJ, Burley SK, Cleveland S, Colwell LJ, Conesa A, Dallago C, Danchin A, de Waard A, Deutschbauer A, Dias R, Ding Y, Fang G, Friedberg I, Gerlt J, Goldford J, Gorelik M, Gyori BM, Henry C, Hutinet G, Jaroch M, Karp PD, Kondratova L, Lu Z, Marchler-bauer A, Martin M, Mcwhite C, Moghe GD, Monaghan P, Morgat A, Mungall CJ, Natale DA, Nelson WC, O’donoghue S, Orengo C, O’toole KH, Radivojac P, Reed C, Roberts RJ, Rodionov D, Rodionova IA, Rudolf JD, Saleh L, Sheynkman G, Thibaud-nissen F, Thomas PD, Uetz P, Vallenet D, Carter EW, Weigele PR, Wood V, Wood-charlson EM, Xu J. A roadmap for the functional annotation of protein families: a community perspective. Database 2022;2022. [DOI: 10.1093/database/baac062] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Armengaud J. Metaproteomics to understand how microbiota function: The crystal ball predicts a promising future. Environ Microbiol 2023;25:115-25. [PMID: 36209500 DOI: 10.1111/1462-2920.16238] [Reference Citation Analysis]
2 Holm L, Laiho A, Törönen P, Salgado M. DALI shines a light on remote homologs: One hundred discoveries. Protein Sci 2023;32:e4519. [PMID: 36419248 DOI: 10.1002/pro.4519] [Reference Citation Analysis]
3 Ferruz N, Heinzinger M, Akdel M, Goncearenco A, Naef L, Dallago C. From sequence to function through structure: deep learning for protein design.. [DOI: 10.1101/2022.08.31.505981] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]