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© Institut Pasteur
Cells infected for 24 hrs with C. Trachomatis. The cell nuclei are labelled in blue, the bacteria appear yellow, within the inclusion lumen. A bacterial protein secreted out the inclusion into the host cytoplasm id labelled in red.
Publication : Acta crystallographica. Section D, Biological crystallography

SPINE bioinformatics and data-management aspects of high-throughput structural biology

Team: Structural Microbiology
Member: Pedro Alzari
Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Acta crystallographica. Section D, Biological crystallography - 19 Sep 2006

Albeck S, Alzari P, Andreini C, Banci L, Berry IM, Bertini I, Cambillau C, Canard B, Carter L, Cohen SX, Diprose JM, Dym O, Esnouf RM, Felder C, Ferron F, Guillemot F, Hamer R, Ben Jelloul M, Laskowski RA, Laurent T, Longhi S, Lopez R, Luchinat C, Malet H, Mochel T, Morris RJ, Moulinier L, Oinn T, Pajon A, Peleg Y, Perrakis A, Poch O, Prilusky J, Rachedi A, Ripp R, Rosato A, Silman I, Stuart DI, Sussman JL, Thierry JC, Thompson JD, Thornton JM, Unger T, Vaughan B, Vranken W, Watson JD, Whamond G, Henrick K

Link to Pubmed [PMID] – 17001095

Acta Crystallogr. D Biol. Crystallogr. 2006 Oct;62(Pt 10):1184-95

SPINE (Structural Proteomics In Europe) was established in 2002 as an integrated research project to develop new methods and technologies for high-throughput structural biology. Development areas were broken down into workpackages and this article gives an overview of ongoing activity in the bioinformatics workpackage. Developments cover target selection, target registration, wet and dry laboratory data management and structure annotation as they pertain to high-throughput studies. Some individual projects and developments are discussed in detail, while those that are covered elsewhere in this issue are treated more briefly. In particular, this overview focuses on the infrastructure of the software that allows the experimentalist to move projects through different areas that are crucial to high-throughput studies, leading to the collation of large data sets which are managed and eventually archived and/or deposited.