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PMID: 17680686 Published · ppublish English Evaluation Study Journal Article Research Support, Non-U.S. Gov't

Assessment of predictions submitted for the CASP7 domain prediction category.

Proteins ·Vol. 69 Suppl 8 ·2007-00-00 ·Pages 137-51

Tress M, Cheng J, Baldi P, Joo K, Lee J, Seo JH, Lee J, Baker D, Chivian D, Kim D, Ezkurdia I

Abstract

This paper details the assessment process and evaluation results for the Critical Assessment of Protein Structure Prediction (CASP7) domain prediction category. Domain predictions were assessed using the Normalized Domain Overlap score introduced in CASP6 and the accuracy of prediction of domain break points. The results of the analysis clearly demonstrate that the best methods are able to make consistently reliable predictions when the target has a structural template, although they are less good when the domain break occurs in a region not covered by a template. The conditions of the experiment meant that it was impossible to draw any conclusions about domain prediction for free modeling targets and it was also difficult to draw many distinctions between the best groups. Two thirds of the targets submitted were single domains and hence regarded as easy to predict. Even those targets defined as having multiple domains always had at least one domain with a similar template structure.

MeSH Terms
Computational Biology/methods Databases, Protein Models, Molecular Protein Folding Protein Structure, Tertiary Proteins/chemistry
Chemicals
Proteins
Authors & Affiliations
11 authors, click to expand affiliations / ORCID
Tress Michael
Structural and Biological Computation Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es
Cheng Jianlin
Baldi Pierre
Joo Keehyoung
Lee Jinwoo
Seo Joo-Hyun
Lee Jooyoung
Baker David
Chivian Dylan
Kim David
Ezkurdia Iakes
Article Info
Journal
Proteins
Abbr.
Proteins
ISSN
1097-0134
Published
2007-00-00
Pages
137-51
Language
English
Region
United States
NLM ID
8700181
Subset
IM
Analysis Services
Analysis Services

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