Applications Of Bibliometrics And Text Mining In The Life Science

In the last decade, with the rapid development in the biomedical science and technology, the biomedical literature showed an exponential growth. Facing with such a large scale and fast-growing literature data, it becomes very difficult to acquire interesting knowledge manually. How to integrate existing knowledge and mining new knowledge from the massive literature has become an important field of bioinformatics.Firstly, bibliometric analysis was performed on the disease-related fundamental research literatures collected in the PubMed to find out the research status, hot spot, core journals, core research institutes, countries with powerful research strength and the future trend. The results for 21 kinds of diseases showed that the number of disease-related fundamental research papers began to rise slowly in 1946 or so, and after 2000 the papers showed significantly faster growth; the powerful research countries and core institutions mainly were located in North America, Europe, and Asia; and in general, the number of publications were related to the gross domestic product positively.Secondly, a method was proposed to extract disease-related genes from massive literatures. This method integrated the previous experimental information based on single genes, and studied the interactions and pathways at the molecular level for disease development and prognosis in a more systematic and comprehensive way. With our proposed method, prostate cancer related genes were extracted and analyzed for the validation of it. The result showed that disease-related genes could be extracted from massive literatures quickly and efficiently with our method. Hence, it was employed to extract the related genes for the aforementioned 21 kinds of diseases.Finally, a disease fundamental research geographic information system was built with the Google Maps API, PHP, Apache, and MySQL technologies . This system integrated the results from the bibliometric analysis and text mining, and provided some ideas or supported information of disease-related fundamental research for biomedical researchers.