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Abstract
Background: At present, all or the majority of published databases report metastasis genes based on the concept of using cancer types or hallmarks of cancer/metastasis. Since tumor metastasis is a dynamic process involving many cellular and molecular processes, those databases cannot provide information on the sequential relations and cellular and molecular mechanisms among different metastasis stages.
Objective: We incorporate the concept of tumor metastasis mechanism to construct a tumor metastasis mechanism-associated gene (TMMG) database based on using the metastasis mechanism concept.
Methods: We utilized the text mining tool, BioBERT to mine the titles and abstracts of the papers and identify TMMGs.
Results: This tumor metastasis mechanism-associated gene database (TMMGdb) contains a wealth of annotations. To check the reliability of TMMGdb, we compared the proportions of housekeeping genes (HKGs) in TMMGdb, HCMDB, and CMgene, the results showed that around 20% of the TMMGs are HKGs, and the proportions are highly consistent among the three databases. Compared with the HCMDB and CMgene databases, TMMGdb is able to find a more recent (on or after 2017) collection of publications and TMMGs. We provided six case studies to illustrate the uniqueness of the TMMGdb database.
Conclusion: TMMGdb is a comprehensive resource for the biomedical community to understand the dynamic process, molecular features, and cellular processes involved in tumor metastasis. TMMGdb provides four interfaces; ‘Browse’, ‘Search’, ‘DEG Search’ and ‘Download’, for users to investigate the causal effects among different metastasis stages; the database is freely accessible at http://hmg.asia.edu.tw/ TMMGdb.
Keywords: Tumor metastasis mechanism, cancer types, text mining, genetic mutations, cancer driver genes, protein-protein interaction networks.
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