Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloA hybrid genetic-neural system for predicting protein secondary structure
Anno di pubblicazione2005
FormatoCartaceo
Autore/iArmano, G; Mancosu, G; Milanesi, L; Orro, A; Saba, M; Vargiu, E
Affiliazioni autoriUniversity of Cagliari; Shardna Life Sci; Consiglio Nazionale delle Ricerche (CNR)
Autori CNR e affiliazioni
  • ALESSANDRO ORRO
  • LUCIANO MILANESI
Lingua/e
  • inglese
AbstractBackground: Due to the strict relation between protein function and structure, the prediction of protein 3D-structure has become one of the most important tasks in bioinformatics and proteomics. In fact, notwithstanding the increase of experiment al data on protein structures available in public databases, the gap between known sequences and known tertiary structures is constantly increasing. The need for automatic methods has brought the development of several prediction and modelling tools, but a general methodology able to solve the problem has not yet been devised, and most methodologies concentrate on the simplified task of predicting secondary structure. Results: In this paper we concentrate on the problem of predicting secondary structures by adopting a technology based on multiple experts. The system performs an overall processing based on two main steps: first, a "sequence-to-structure" prediction is enforced by resorting to a population of hybrid (genetic-neural) experts, and then a "structure-to-structure" prediction is performed by resorting to an artificial neural network. Experiments, performed on sequences taken from well-known protein databases, allowed to reach an accuracy of about 76%, which is comparable to those obtained by state-of-the-art predictors. Conclusion: The adoption of a hybrid technique, which encompasses genetic and neural technologies, has demonstrated to be a promising approach in the task of protein secondary structure prediction
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da-
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Pagine totali7
RivistaBMC bioinformatics
Attiva dal 2000
Editore: BioMed Central, - [London]
Paese di pubblicazione: Regno Unito
Lingua: inglese
ISSN: 1471-2105
Titolo chiave: BMC bioinformatics
Titolo proprio: BMC bioinformatics
Titolo abbreviato: BMC bioinformatics
Titoli alternativi:
  • BioMed Central bioinformatics
  • Bioinformatics
Numero volume della rivista6
Fascicolo della rivista-
DOI10.1186/1471-2105-6-S4-S3
Verificato da refereeSì: Internazionale
Stato della pubblicazione-
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000236064600003)
Parole chiaveBioinformatics, Protein, Genetics, Neural, symulation
Link (URL, URI)-
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • ITB — Istituto di tecnologie biomediche
Moduli/Attività/Sottoprogetti CNR
  • PM.P06.010.001 : Applicazioni della Bioinformatica e Neuroinformatica al GRID computing
  • ME.P06.027.001 : Bioinformatica in Biomedicina
Progetti Europei-
Allegati
Hybrid Genetic-Neural System for Predicting Protein Secondary Structure.
Descrizione: Articolo
Tipo documento: application/pdf

Dati storici
I dati storici non sono modificabili, sono stati ereditati da altri sistemi (es. Gestione Istituti, PUMA, ...) e hanno solo valore storico.
Area disciplinareComputer Science & Engineering
Area valutazione CIVRScienze biologiche
Rivista ISIBMC BIOINFORMATICS [00006NN]