An Automated Tool for Scoring Biomedical Terms Correlation Based on Semantic Analysis

The considerable improvement in the biotechnogical field and the adoption of screen techniques such as high throughput arrays produced a spread of biological and genetical data and scientific papers, mostly diffused on the Web. Even if the huge amount of available information represents a major step forward for the biomedical research field, the main effort for a scientist is to evaluate the correlation among the concepts both in qualitative and in quantitative terms. In the presented work, exploiting the richness of the UMLS Metathesaurus in combination with the novelty of the literature provided by PubMed, an automatic flow aimed at the scoring the semantic correlation among biomedical terms (e. g. biomolecules and biological processes) is proposed. The experiments show that obtained correlations are fully coherent with the information coming from the biological literature. The accuracy of the results remarks the importance of combining text mining techniques with complete and well structured thesaurus, such as UMLS.