  Genome-wide association (GWA) constitutes a prominent portion of studies
which have been conducted on personalized medicine and pharmacogenomics.
Recently, very few methods have been developed for extracting mutation-diseases
associations. However, there is no available method for extracting the
association of SNP-phenotype from text which considers degree of confidence in
associations. In this study, first a relation extraction method relying on
linguistic-based negation detection and neutral candidates is proposed. The
experiments show that negation cues and scope as well as detecting neutral
candidates can be employed for implementing a superior relation extraction
method which outperforms the kernel-based counterparts due to a uniform innate
polarity of sentences and small number of complex sentences in the corpus.
Moreover, a modality based approach is proposed to estimate the confidence
level of the extracted association which can be used to assess the reliability
of the reported association. Keywords: SNP, Phenotype, Biomedical Relation
Extraction, Negation Detection.
