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RONN : the bio-basis function neural network technique applied to the detection of natively disordered regions in proteins

Author
ZHENG RONG YANG1 ; THOMSON, Rebecca2 ; MCNEIL, Philip3 ; ESNOUF, Robert M2
[1] School of Engineering and Computer Science, Exeter University, Exeter EX4 4QF, United Kingdom
[2] Division of Structural Biology and Oxford Protein Production Facility, University of Oxford, Henry Wellcome Building for Genomic Medicine, Roosevelt Drive, Oxford OX3 7BN, United Kingdom
[3] European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton , Cambridge CB10 1SD, United Kingdom
Source

Bioinformatics (Oxford. Print). 2005, Vol 21, Num 16, pp 3369-3376, 8 p ; ref : 42 ref

ISSN
1367-4803
Scientific domain
Bioinformatics
Publisher
Oxford University Press, Oxford
Publication country
United Kingdom
Document type
Article
Language
English
Keyword (fr)
Analyse structurale Désordre Détection Etat natif Protéine Réseau neuronal Solubilité Structure 3 dimensions
Keyword (en)
Structural analysis Disorder Detection Native state Protein Neural network Solubility Three dimensional structure
Keyword (es)
Análisis estructural Desorden Detección Estado nativo Proteína Red neuronal Solubilidad Estructura 3 dimensiones
Classification
Pascal
002 Biological and medical sciences / 002A Fundamental and applied biological sciences. Psychology / 002A01 General aspects / 002A01B Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)

Discipline
Biological sciences. Generalities. Modelling. Methods Generalities in biological sciences
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
17033547

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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