About: SPINE bioinformatics and data‐management aspects of high‐throughput structural biology

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	SPINE bioinformatics and data‐management aspects of high‐throughput structural biology
Creator	Watson, J Cohen, S Canard, B Thompson, J Cambillau, C Malet, H Stuart, D Bertini, I Peleg, Y Perrakis, A Sussman, J Thornton, J Carter, L Ferron, F Alzari, P Dym, O Albeck, S Andreini, C Banci, L Berry, I Diprose, J Esnouf, R Felder, C Guillemot, F Hamer, R Henrick, K Jelloul, M Laskowski, R Laurent, T Longhi, S Lopez, R Luchinat, C Mochel, T Morris, R Moulinier, L Oinn, T Pajon, A Poch, O Prilusky, J Rachedi, A Ripp, R Rosato, A Silman, I Thierry, J.-C Unger, T Vaughan, B Vranken, W Whamond, G
topic	covid:e85f7f54a5f9a81887157de85ef4e39a0ef42a1a#this
Source	PMC
abstract	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.
has issue date	2006-10-04(xsd:dateTime)
bibo:doi	10.1107/s090744490602991x
bibo:pmid	17001095
has license	no-cc
sha1sum (hex)	e85f7f54a5f9a81887157de85ef4e39a0ef42a1a
schema:url	https://doi.org/10.1107/s090744490602991x
resource representing a document's title	SPINE bioinformatics and data‐management aspects of high‐throughput structural biology
has PubMed Central identifier	PMC7161634
has PubMed identifier	17001095
schema:publication	Acta Crystallogr D Biol Crystallogr
resource representing a document's body	covid:e85f7f54a5f9a81887157de85ef4e39a0ef42a1a#body_text
is http://vocab.deri.ie/void#inDataset of	https://covidontheweb.inria.fr:4443/about/id/http/ns.inria.fr/covid19/e85f7f54a5f9a81887157de85ef4e39a0ef42a1a
is schema:about of	named entity 'cover' named entity 'Crystallography' named entity 'high-throughput' named entity 'PARTICULAR' named entity 'HIGH' named entity 'MOVE' named entity 'detail' named entity '2002' named entity 'projects' named entity 'bioinformatics' named entity 'laboratory' named entity 'high-throughput' named entity 'experimentalist' named entity 'selection' named entity 'developments' named entity 'bioinformatics' named entity 'large data sets' named entity 'Europe' named entity 'Structural Proteomics' named entity 'E. coli' named entity 'ALICE' named entity 'PCR' named entity 'EBI' named entity 'drums' named entity 'structural proteomics' named entity 'bioinformatics' named entity 'ProFunc' named entity 'data-management' named entity 'high-throughput' named entity 'organism' named entity 'GenBank' named entity 'homology'

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