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Database Profile

General information

URL: http://wakanmoview.inm.u-toyama.ac.jp/kampo
Full name: Kampo Database
Description: a novel platform for the analysis of natural medicines, which provides various useful scientific resources on Japanese traditional formulas Kampo medicines, constituent herbal drugs, constituent compounds, and target proteins of these constituent compounds.
Year founded: 2018
Last update:
Version:
Accessibility:
Manual:
Accessible
Real time : Checking...
Country/Region: Japan

Classification & Tag

Data type:
Data object:
NA
Database category:
Major species:
NA
Keywords:

Contact information

University/Institution: Kyushu Institute of Technology
Address:
City:
Province/State:
Country/Region: Japan
Contact name (PI/Team): Yoshihiro Yamanishi
Contact email (PI/Helpdesk):

Publications

30046160
KampoDB, database of predicted targets and functional annotations of natural medicines. [PMID: 30046160]
Ryusuke Sawada, Michio Iwata, Masahito Umezaki, Yoshihiko Usui, Toshikazu Kobayashi, Takaki Kubono, Shusaku Hayashi, Makoto Kadowaki, Yoshihiro Yamanishi

Natural medicines (i.e., herbal medicines, traditional formulas) are useful for treatment of multifactorial and chronic diseases. Here, we present KampoDB ( http://wakanmoview.inm.u-toyama.ac.jp/kampo/ ), a novel platform for the analysis of natural medicines, which provides various useful scientific resources on Japanese traditional formulas Kampo medicines, constituent herbal drugs, constituent compounds, and target proteins of these constituent compounds. Potential target proteins of these constituent compounds were predicted by docking simulations and machine learning methods based on large-scale omics data (e.g., genome, proteome, metabolome, interactome). The current version of KampoDB contains 42 Kampo medicines, 54 crude drugs, 1230 constituent compounds, 460 known target proteins, and 1369 potential target proteins, and has functional annotations for biological pathways and molecular functions. KampoDB is useful for mode-of-action analysis of natural medicines and prediction of new indications for a wide range of diseases.

Sci Rep. 2018:8(1) | 7 Citations (from Europe PMC, 2024-04-06)

Ranking

All databases:
4018/6000 (33.05%)
Pathway:
248/389 (36.504%)
Health and medicine:
920/1394 (34.075%)
4018
Total Rank
7
Citations
1.167
z-index

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Record metadata

Created on: 2019-01-04
Curated by:
Dong Zou [2019-01-12]
Dong Zou [2019-01-04]