Artículo
The articles.ELM resource: Simplifying access to protein linear motif literature by annotation, text-mining and classification
Palopoli, Nicolás
; Iserte, Javier Alonso
; Chemes, Lucia Beatriz
; Marino Buslje, Cristina; Parisi, Gustavo Daniel
; Gibson, Toby James; Davey, N.E.
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Fecha de publicación:
01/2020
Editorial:
Oxford University Press
Revista:
Database
ISSN:
1758-0463
e-ISSN:
1758-0463
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
Modern biology produces data at a staggering rate. Yet, much of these biological data is still isolated in the text, figures, tables and supplementary materials of articles. As a result, biological information created at great expense is significantly underutilised. The protein motif biology field does not have sufficient resources to curate the corpus of motif-related literature and, to date, only a fraction of the available articles have been curated. In this study, we develop a set of tools and a web resource, 'articles.ELM', to rapidly identify the motif literature articles pertinent to a researcher's interest. At the core of the resource is a manually curated set of about 8000 motif-related articles. These articles are automatically annotated with a range of relevant biological data allowing in-depth search functionality. Machine-learning article classification is used to group articles based on their similarity to manually curated motif classes in the Eukaryotic Linear Motif resource. Articles can also be manually classified within the resource. The 'articles.ELM' resource permits the rapid and accurate discovery of relevant motif articles thereby improving the visibility of motif literature and simplifying the recovery of valuable biological insights sequestered within scientific articles. Consequently, this web resource removes a critical bottleneck in scientific productivity for the motif biology field.
Palabras clave:
LINEAR MOTIF
,
TEXT MINING
,
DATABASE
,
DISCOVERY
Archivos asociados
Licencia
Identificadores
Colecciones
Articulos (IIBIO)
Articulos de INSTITUTO DE INVESTIGACIONES BIOTECNOLOGICAS
Articulos de INSTITUTO DE INVESTIGACIONES BIOTECNOLOGICAS
Articulos(IIBBA)
Articulos de INST.DE INVEST.BIOQUIMICAS DE BS.AS(I)
Articulos de INST.DE INVEST.BIOQUIMICAS DE BS.AS(I)
Citación
Palopoli, Nicolás; Iserte, Javier Alonso; Chemes, Lucia Beatriz; Marino Buslje, Cristina; Parisi, Gustavo Daniel; et al.; The articles.ELM resource: Simplifying access to protein linear motif literature by annotation, text-mining and classification; Oxford University Press; Database; 2020; 1-2020; 1-10
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