PRED-CLASS: cascading neural networks for generalized protein classification and genome-wide applications

Abstract : A cascading system of hierarchical, artificial neural networks (named PRED-CLASS) is presented for the generalized classification of proteins into four distinct classes-transmembrane, fibrous, globular, and mixed-from information solely encoded in their amino acid sequences. The architecture of the individual component networks is kept very simple, reducing the number of free parameters (network synaptic weights) for faster training, improved generalization, and the avoidance of data overfitting. Capturing information from as few as 50 protein sequences spread among the four target classes (6 transmembrane, 10 fibrous, 13 globular, and 17 mixed), PRED-CLASS was able to obtain 371 correct predictions out of a set of 387 proteins (success rate approximately 96%) unambiguously assigned into one of the target classes. The application of PRED-CLASS to several test sets and complete proteomes of several organisms demonstrates that such a method could serve as a valuable tool in the annotation of genomic open reading frames with no functional assignment or as a preliminary step in fold recognition and ab initio structure prediction methods. Detailed results obtained for various data sets and completed genomes, along with a web sever running the PRED-CLASS algorithm, can be accessed over the World Wide Web at http://o2.biol.uoa.gr/PRED-CLASS.
Type de document :
Article dans une revue
Proteins - Structure, Function and Bioinformatics, Wiley, 2001, 44 (3), pp.361-9. 〈10.1002/prot.1101〉
Liste complète des métadonnées

Littérature citée [30 références]  Voir  Masquer  Télécharger

https://hal.archives-ouvertes.fr/hal-00170747
Contributeur : Claude Pasquier <>
Soumis le : mercredi 18 février 2009 - 14:48:22
Dernière modification le : lundi 25 mai 2015 - 07:23:34
Document(s) archivé(s) le : vendredi 25 novembre 2016 - 18:17:01

Fichiers

predclass-final.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Citation

Claude Pasquier, Vasilis Promponas, Stavros Hamodrakas. PRED-CLASS: cascading neural networks for generalized protein classification and genome-wide applications. Proteins - Structure, Function and Bioinformatics, Wiley, 2001, 44 (3), pp.361-9. 〈10.1002/prot.1101〉. 〈hal-00170747〉

Partager

Métriques

Consultations de la notice

103

Téléchargements de fichiers

57