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BioProber2.0: a unified biomedical workbench with mining and probing literatures

The number of biomedical literatures is increasing at a considerable rate, and the information is growing continuously and fast as well. Accordingly, information retrieval is more and more important to support biomedical researches. However, it often retrieves too many literatures or too few literatures for the target gene/proteins or relations. And extremely various synonyms of the gene and protein names make information retrieval more difficult to support biomedical researches. To overcome these difficulties, we propose a unified biomedical workbench with mining and probing literatures. The proposed workbench is composed of searching/collecting, literature mining, relation probing, and statistics analysis. It provides searching and collecting literatures of Pubmed articles and USPTO patents. And, to extract biomedical relations, the collected literatures are mined using text mining techniques such as named entity recognition, gene/protein name normalization, and relation extraction. Users can probe their target relations using these extracted relation information, shown in form of relation network. Finally, the workbench provides statistics information of literature meta data such as authors, organizations, publication years and so on. That is, the proposed workbench provides unified literature-based functions from searching to probing, and including text mining and statistics analysis.