QsarDB is developing and operates domain-specific digital data exchange standards and tools that enables research groups, project teams and institutions to share and present Quantitative Structure-Activity Relationships (data and models):
The QSAR DataBank (QsarDB) repository aims to make the processes and outcomes of in silico modelling work transparent, reproducible and accessible.
The models are represented in the QsarDB data format and stored in a content-aware repository.
The repository in addition to browsing and downloading models also offers integrated services, such as model analysis and visualization and making predictions.
The QsarDB repository unlocks the potential of descriptive and predictive in silico (Q)SAR models by allowing new and different types of collaboration between model developers and model users.
QsarDB makes in silico (Q)SAR models citable via unique and persistent identifiers (HDL and DOI)
The QsarDB repository automates most of the unexciting work (e.g., collecting, systematizing, and reporting data), thereby reducing the time to decision.
The QsarDB repository is designed for models produced with all statistical and mathematical algorithms that qualitatively or quantitatively express the relationship between the chemical structure and the responses of a compound. This information includes chemico-biological activity (QSAR), physicochemical properties (QSPR), toxicity (QSTR), metabolism (QSMR), reactivity (QSRR), retention (QSRR), permeability (QSPR), pharmacokinetics (QSPR), bioavailability (QSBR), binding (QSBR), etc.