Complex Network Study of the Immune Epitope Database for Parasitic Organisms.
Curr Top Med Chem
; 17(30): 3249-3255, 2018 Feb 09.
Article
em En
| MEDLINE
| ID: mdl-29231143
BACKGROUND: Complex network approach allows the representation and analysis of complex systems of interacting agents in an ordered and effective manner, thus increasing the probability of discovering significant properties of them. In the present study, we defined and built for the first time a complex network based on data obtained from Immune Epitope Database for parasitic organisms. We then considered the general topology, the node degree distribution, and the local structure (triadic census) of this network. In addition, we calculated 9 node centrality measures for observed network and reported a comparative study of the real network with three theoretical models to detect similarities or deviations from these ideal networks. RESULT: The results obtained corroborate the utility of the complex network approach for handling information and data mining within the database under study. CONCLUSION: They confirm that this type of approach can be considered a valuable tool for preliminary screening of the best experimental conditions to determine whether the amino acid sequences being studied are true epitopes or not.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Parasitos
/
Bases de Dados Factuais
/
Redes Neurais de Computação
/
Epitopos
Limite:
Animals
Idioma:
En
Revista:
Curr Top Med Chem
Assunto da revista:
QUIMICA
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
Argentina
País de publicação:
Emirados Árabes Unidos