InforLorV4, Main, Exploration, bibRecord, 002D28

SHREC'10 Track: Protein Models

Identifieur interne : 002D28 ( Main/Exploration ); précédent : 002D27; suivant : 002D29

SHREC'10 Track: Protein Models

Auteurs : Lazaros Mavridis [France] ; Vishwesh Venkatraman [France] ; David Ritchie [France] ; H. Morikawa [Japon] ; Rumen Andonov [France] ; Alexandre Cornu [France] ; Noël Malod-Dognin [France] ; Jacques Nicolas [France] ; M. Temerinac-Ott [Allemagne] ; M. Reisert [Allemagne] ; H. Burkhardt [Allemagne] ; A. Axenopoulos [Grèce] ; P. Daras [Grèce]

Source :

RBID : Hal:inria-00536680

Abstract

This paper presents the results of the SHREC'10 Protein Models Classification Track. The aim of this track is to evaluate how well 3D shape recognition algorithms can classify protein structures according to the CATH [CSL08] superfamily classification. Five groups participated in this track, using a total of six methods, and for each method a set of ranked predictions was submitted for each classification task. The evaluation of each method is based on the nearest neighbour and area under the curve(AUC) metrics.

Url:

https://hal.inria.fr/inria-00536680

Affiliations:

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Le document en format XML

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<country>Allemagne</country>
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<country>Grèce</country>
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<front><div type="abstract" xml:lang="en">This paper presents the results of the SHREC'10 Protein Models Classification Track. The aim of this track is to evaluate how well 3D shape recognition algorithms can classify protein structures according to the CATH [CSL08] superfamily classification. Five groups participated in this track, using a total of six methods, and for each method a set of ranked predictions was submitted for each classification task. The evaluation of each method is based on the nearest neighbour and area under the curve(AUC) metrics.</div>
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SHREC'10 Track: Protein Models

SHREC'10 Track: Protein Models

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