Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Tea is one of the most popular non-alcoholic beverages consumed worldwide. Numerous bioactive constituents of tea were confirmed to possess healthy benefits via the mechanisms of regulating gene expressions or protein activities. However, a complete interacting profile between tea bioactive compounds (TBCs) and their target genes is lacking, which put an obstacle in the study of healthy function of tea. To fill this gap, we developed a database of target genes of TBCs (TBC2target, http://camellia.ahau.edu.cn/TBC2target) based on a pharmacophore mapping approach. In TBC2target, 6,226 interactions between 240 TBCs and 673 target genes were documented. TBC2target contains detailed information about each interacting entry, such as TBC, CAS number, PubChem CID, source of compound (e.g., green, black), compound type, target gene(s) of TBC, gene symbol, gene ID, ENSEMBL ID, PDB ID, TBC bioactivity and the reference. Using the TBC-target associations, we constructed a bipartite network and provided users the global network and local sub-network visualization and topological analyses. The entire database is free for online browsing, searching and downloading. In addition, TBC2target provides a BLAST search function to facilitate use of the database. The particular strengths of TBC2target are the inclusion of the comprehensive TBC-target interactions, and the capacity to visualize and analyze the interacting networks, which may help uncovering the beneficial effects of tea on human health as a central resource in tea health community.
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