Abstract
A multi-layered biomedical literature mining approach is presented aiming to the discovery of gene-gene correlations and the construction of respective gene networks. Utilization of the Trie-memory data structure enables efficient manipulation of different gene nomenclatures. The whole approach is coupled with a texts (biomedical abstracts) classification method. Experimental validation and evaluation results show the rationality, efficiency and reliability of the approach.
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