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Cell Mol Life Sci. 2010 Apr;67(7):1049-64. doi: 10.1007/s00018-009-0229-6. Epub 2009 Dec 31.

From protein sequences to 3D-structures and beyond: the example of the UniProt knowledgebase.

Collaborators (135)

Apweiler R, Martin MJ, O'Donovan C, Magrane M, Alam-Faruque Y, Antunes R, Barrell D, Bely B, Bingley M, Binns D, Bower L, Browne P, Chan WM, Dimmer E, Eberhardt R, Fedotov A, Foulger R, Garavelli J, Huntley R, Jacobsen J, Kleen M, Laiho K, Leinonen R, Legge D, Lin Q, Liu W, Luo J, Orchard S, Patient S, Poggioli D, Pruess M, Corbett M, di Martino G, Donnelly M, van Rensburg P, Bairoch A, Bougueleret L, Xenarios I, Altairac S, Auchincloss A, Argoud-Puy G, Axelsen K, Baratin D, Blatter MC, Boeckmann B, Bolleman J, Bollondi L, Boutet E, Quintaje SB, Breuza L, Bridge A, de Castro E, Ciapina L, Coral D, Coudert E, Cusin I, David F, Delbard G, Doche M, Dornevil D, Roggli PD, Duvaud S, Estreicher A, Famiglietti L, Feuermann M, Gehant S, Farriol-Mathis N, Ferro S, Gasteiger E, Gateau A, Gerritsen V, Gos A, Gruaz-Gumowski N, Hinz U, Hulo C, Hulo N, James J, Jimenez S, Jungo F, Kappler T, Keller G, Lachaize C, Lane-Guermonprez L, Langendijk-Genevaux P, Lara V, Lemercier P, Lieberherr D, Lima Tde O, Mangold V, Martin X, Masson P, Moinat M, Morgat A, Mottaz A, Paesano S, Pedruzzi I, Pilbout S, Pillet V, Poux S, Pozzato M, Redaschi N, Rivoire C, Roechert B, Schneider M, Sigrist C, Sonesson K, Staehli S, Stanley E, Stutz A, Sundaram S, Tognolli M, Verbregue L, Veuthey AL, Yip L, Zuletta L, Wu C, Arighi C, Arminski L, Barker W, Chen C, Chen Y, Hu ZZ, Huang H, Mazumder R, McGarvey P, Natale DA, Nchoutmboube J, Petrova N, Subramanian N, Suzek BE, Ugochukwu U, Vasudevan S, Vinayaka CR, Yeh LS, Zhang J.

Author information

Swiss-Prot Group, Swiss Institute of Bioinformatics, 1 rue Michel Servet, 1211, Geneva, Switzerland.


With the dramatic increase in the volume of experimental results in every domain of life sciences, assembling pertinent data and combining information from different fields has become a challenge. Information is dispersed over numerous specialized databases and is presented in many different formats. Rapid access to experiment-based information about well-characterized proteins helps predict the function of uncharacterized proteins identified by large-scale sequencing. In this context, universal knowledgebases play essential roles in providing access to data from complementary types of experiments and serving as hubs with cross-references to many specialized databases. This review outlines how the value of experimental data is optimized by combining high-quality protein sequences with complementary experimental results, including information derived from protein 3D-structures, using as an example the UniProt knowledgebase (UniProtKB) and the tools and links provided on its website ( ). It also evokes precautions that are necessary for successful predictions and extrapolations.

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