An intelligent agent-based biomedical literature mining system for cancer-related genes

Cancer has now become the major disease threatening people´s health. That is why research on the factor causing cancer has become significant. Although biomedical researchers can obtain a lot of related biomedical literature through a search engine, they also have to face the problem of information overload as well. We propose an intelligent agent system regarding the data mining of biomedical literature, hoping to provide assistance. According to the type of cancer user enter, the system will automatically combine it with LOH (loss of heterozygosity) or CGH (comparative genomic hybridization), and then search for related biomedical literatures from the PubMed. And then the retrieved literatures will be categorized using the decision tree, with which the cancer-related genes can be mined at the same time. The method can help mine important information from biomedical literatures and thus helps users to gain quick and easy access to important information. Also, this method can be applied to other diseases.