Limits...
Event-based text mining for biology and functional genomics.

Ananiadou S, Thompson P, Nawaz R, McNaught J, Kell DB - Brief Funct Genomics (2014)

Bottom Line: This article provides an overview of recent research into event extraction.We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems.Finally, several concrete applications of event extraction are covered, together with emerging directions of research.

View Article: PubMed Central - PubMed

No MeSH data available.


iHop search interface, showing results retrieved by search for SNF1. Additional entities, MeSH terms, interactions and words are highlighted. (A colour version of this figure is available online at: http://bfg.oxfordjournals.org)
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4499874&req=5

elu015-F6: iHop search interface, showing results retrieved by search for SNF1. Additional entities, MeSH terms, interactions and words are highlighted. (A colour version of this figure is available online at: http://bfg.oxfordjournals.org)

Mentions: Semantic search systems allow much more precise and focused retrieval and extraction than do the traditional keyword-based systems [112]. Earlier systems aimed to increase the number of hits retrieved by a user’s query, through automatic query expansion with synonyms or variants of query terms. Automatic identification of other terms and/or interaction-indicating verbs in the same sentence or abstract can allow identification of potential events or associations involving search terms. iHOP (http://www.ihop-net.org) [23, 113] highlights additional terms and verbs in sentences retrieved by searching for a gene (see Figure 6), whereas FACTA+ (http://www.nactem.ac.uk/facta/) [15] calculates and visualises strengths of association between a search term and other important concepts (e.g. genes, diseases and chemical compounds), by finding abstract-level co-occurrences over the whole of the MEDLINE abstract database. FACTA+ queries can be refined through specification that event(s) of a particular type should be present in the abstracts retrieved. For example, the query ‘ERK2 GENIA:Positive_regulation’ will retrieve abstracts containing both the term ‘ERK2’ and an event of type ‘Positive regulation’.Figure 6:


Event-based text mining for biology and functional genomics.

Ananiadou S, Thompson P, Nawaz R, McNaught J, Kell DB - Brief Funct Genomics (2014)

iHop search interface, showing results retrieved by search for SNF1. Additional entities, MeSH terms, interactions and words are highlighted. (A colour version of this figure is available online at: http://bfg.oxfordjournals.org)
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4499874&req=5

elu015-F6: iHop search interface, showing results retrieved by search for SNF1. Additional entities, MeSH terms, interactions and words are highlighted. (A colour version of this figure is available online at: http://bfg.oxfordjournals.org)
Mentions: Semantic search systems allow much more precise and focused retrieval and extraction than do the traditional keyword-based systems [112]. Earlier systems aimed to increase the number of hits retrieved by a user’s query, through automatic query expansion with synonyms or variants of query terms. Automatic identification of other terms and/or interaction-indicating verbs in the same sentence or abstract can allow identification of potential events or associations involving search terms. iHOP (http://www.ihop-net.org) [23, 113] highlights additional terms and verbs in sentences retrieved by searching for a gene (see Figure 6), whereas FACTA+ (http://www.nactem.ac.uk/facta/) [15] calculates and visualises strengths of association between a search term and other important concepts (e.g. genes, diseases and chemical compounds), by finding abstract-level co-occurrences over the whole of the MEDLINE abstract database. FACTA+ queries can be refined through specification that event(s) of a particular type should be present in the abstracts retrieved. For example, the query ‘ERK2 GENIA:Positive_regulation’ will retrieve abstracts containing both the term ‘ERK2’ and an event of type ‘Positive regulation’.Figure 6:

Bottom Line: This article provides an overview of recent research into event extraction.We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems.Finally, several concrete applications of event extraction are covered, together with emerging directions of research.

View Article: PubMed Central - PubMed

No MeSH data available.