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Dimension reduction methods including feature selection and feature extraction have played an important role in data mining and pattern recognition. In this study, we propose a novel unsupervised feature selection approach based on sparse representation theory, namely Sparsity Score (SS). Due to the sparse representation procedure, SS not only owns the(More)
Ontology is widely used in semantic computing and reasoning, and various biomedicine ontologies have become institutionalized to make the heterogeneous knowledge computationally amenable. Relation words, especially verbs, play an important role when describing the interaction between biological entities in molecular function, biological process, and(More)
Polyadenylation [poly(A)] of mRNA is a critical step during gene expression, which plays an important role in the termination of transcription. Prediction of poly(A) sites can help identify 3' ends of genes and improve genome annotation. Due to the limited knowledge of poly(A) signals in plants, predictive modeling of poly(A) sites in agricultural crops(More)
Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identification of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifies and organises words of various proteins interaction(More)
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