SNPPhenA: a corpus for extracting ranked associations of single-nucleotide polymorphisms and phenotypes from literature

SNPPhenA: a corpus for extracting ranked associations of single-nucleotide polymorphisms and phenotypes from literature

Abstract Background Single Nucleotide Polymorphisms (SNPs) are among the most important types of genetic variations influencing common diseases and phenotypes. Recently, some corpora and methods have been developed with the purpose of extracting mutations and diseases from texts. However, there is n...

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Bibliographic Details
Main Authors: Behrouz Bokharaeian, Alberto Diaz, Nasrin Taghizadeh, Hamidreza Chitsaz, Ramyar Chavoshinejad
Format: Article
Language:English
Published: BMC 2017-04-01
Series:Journal of Biomedical Semantics
Subjects:
SNP
Phenotype
Relation extraction
Negation
Modality
Degree of confidence
Online Access:http://link.springer.com/article/10.1186/s13326-017-0116-2

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