Metabobank is a blockchain based database for storing, sharing,
and governing of mass spectra data of endogenous metabolites, especially from plants.
The database has collected structure, synonyms and MS/MS data for around 230,000 compounds, including more than 10,000 high resolution MS//MS data of plant secondary metabolites acquired from standards with multiple acquisition strategies.
The website provides a user data management solution with greater security and flexibility based on blockchain consensus mechanism, which could efficiently guarantee the security of private data, and provides a feasible way for valuable data co-production, sharing and capitalization.
The website also provides a one-stop data processing system for metabolomics and further statistic analysis directly from raw data, which can significantly simplify the analysis process of MS data.
Besides, we also provide a platform for co-production and sharing of AI-based tools based on our database, hoping to gradually solve the challenges of metabolomics analysis, such as metabolite identification, unknown compound prediction, comparison and combination of different bathes, absolute quantification in untargeted analysis, and etc.
We will continuously update the database, annotation methods and AI tools, to meet the growing and evolving demands of plant metabolomics.
The database has collected structure, synonyms and MS/MS data for around 230,000 compounds, including more than 10,000 high resolution MS//MS data of plant secondary metabolites acquired from standards with multiple acquisition strategies.
The website provides a user data management solution with greater security and flexibility based on blockchain consensus mechanism, which could efficiently guarantee the security of private data, and provides a feasible way for valuable data co-production, sharing and capitalization.
The website also provides a one-stop data processing system for metabolomics and further statistic analysis directly from raw data, which can significantly simplify the analysis process of MS data.
Besides, we also provide a platform for co-production and sharing of AI-based tools based on our database, hoping to gradually solve the challenges of metabolomics analysis, such as metabolite identification, unknown compound prediction, comparison and combination of different bathes, absolute quantification in untargeted analysis, and etc.
We will continuously update the database, annotation methods and AI tools, to meet the growing and evolving demands of plant metabolomics.
Address. No 7,Pengfei Road,Dapeng District,Shenzhen
Zip code: 518120
Tel:+860755-23250159 +860755-23250160
Fax:+860755-23251430
E-mail: jys@agis.org.cn
Zip code: 518120
Tel:+860755-23250159 +860755-23250160
Fax:+860755-23251430
E-mail: jys@agis.org.cn