LAITOR--Literature Assistant for Identification of Terms co-Occurrences and Relationships.
BMC Bioinformatics
; 11: 70, 2010 Feb 01.
Article
en En
| MEDLINE
| ID: mdl-20122157
ABSTRACT
BACKGROUND:
Biological knowledge is represented in scientific literature that often describes the function of genes/proteins (bioentities) in terms of their interactions (biointeractions). Such bioentities are often related to biological concepts of interest that are specific of a determined research field. Therefore, the study of the current literature about a selected topic deposited in public databases, facilitates the generation of novel hypotheses associating a set of bioentities to a common context.RESULTS:
We created a text mining system (LAITOR Literature Assistant for Identification of Terms co-Occurrences and Relationships) that analyses co-occurrences of bioentities, biointeractions, and other biological terms in MEDLINE abstracts. The method accounts for the position of the co-occurring terms within sentences or abstracts. The system detected abstracts mentioning protein-protein interactions in a standard test (BioCreative II IAS test data) with a precision of 0.82-0.89 and a recall of 0.48-0.70. We illustrate the application of LAITOR to the detection of plant response genes in a dataset of 1000 abstracts relevant to the topic.CONCLUSIONS:
Text mining tools combining the extraction of interacting bioentities and biological concepts with network displays can be helpful in developing reasonable hypotheses in different scientific backgrounds.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Programas Informáticos
/
Almacenamiento y Recuperación de la Información
/
Minería de Datos
Tipo de estudio:
Diagnostic_studies
/
Systematic_reviews
País/Región como asunto:
America do norte
Idioma:
En
Revista:
BMC Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2010
Tipo del documento:
Article
País de afiliación:
Alemania