Association rules to identify receptor and ligand structures through named entities recognition

Authors:
A. T. Winck;K. S. Machado;D. D. Ruiz;V. L. Strube de Lima
Affiliations:
Pontifícia Universidade Católica do Rio Grande do Sul, Brazil;Pontifícia Universidade Católica do Rio Grande do Sul, Brazil;Pontifícia Universidade Católica do Rio Grande do Sul, Brazil;Pontifícia Universidade Católica do Rio Grande do Sul, Brazil
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Year:
2010

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Abstract

One of the challenges in natural language processing (NLP) is to semantically treat documents. Such process is tailored to specific domains, where bioinformatics appears as a promising interest area. We focus this work on the rational drug design process, in trying to help the identification of new target proteins (receptors) and drug candidate compounds (ligands) in scientific documents. Our approach is to handle such structures as named entities (NE) in the text.We propose the recognition of these NE by analyzing their context. In doing so, considering an annotated corpus on the RDD domain, we present models generated by association rules mining that indicate which terms relevant to the context point out the presence of a receptor or ligand in a sentence.