GROOLS: reactive graph reasoning for genome annotation through biological processes.
BMC Bioinformatics
; 19(1): 132, 2018 04 11.
Article
em En
| MEDLINE
| ID: mdl-29642842
ABSTRACT
BACKGROUND:
High quality functional annotation is essential for understanding the phenotypic consequences encoded in a genome. Despite improvements in bioinformatics methods, millions of sequences in databanks are not assigned reliable functions. The curation of protein functions in the context of biological processes is a way to evaluate and improve their annotation.RESULTS:
We developed an expert system using paraconsistent logic, named GROOLS (Genomic Rule Object-Oriented Logic System), that evaluates the completeness and the consistency of predicted functions through biological processes like metabolic pathways. Using a generic and hierarchical representation of knowledge, biological processes are modeled in a graph from which observations (i.e. predictions and expectations) are propagated by rules. At the end of the reasoning, conclusions are assigned to biological process components and highlight uncertainties and inconsistencies. Results on 14 microbial organisms are presented.CONCLUSIONS:
GROOLS software is designed to evaluate the overall accuracy of functional unit and pathway predictions according to organism experimental data like growth phenotypes. It assists biocurators in the functional annotation of proteins by focusing on missing or contradictory observations.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Fenômenos Biológicos
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Algoritmos
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Software
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Genoma
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Biologia Computacional
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Anotação de Sequência Molecular
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
BMC Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
França