Welcome to QSAR DataBank
QsarDB is a smart repository for (Q)SAR/QSPR models and datasets, ready for discovery, exploring, citing and predicting.
Transparent QSAR data
Create and upload QDB archive
The QsarDB repository requires your model and associated data to be organized. A small effort will make your research transparent and usable.
Explore chemicals
Search from 40000 structures in QDB archives
Exact chemical search, similarity and substructure searches find QDB archives containing the query compound.
Recent submissions
Show your study on this list
- 06 Nov 2019
- Käärik, M.; Arulepp, M.; Käärik, M.; Maran, U.; Leis, J. Characterization and prediction of double-layer capacitance of nanoporous carbon materials using the Quantitative nano-Structure-Property Relationship approach based on experimentally determined porosity descriptors. Carbon 2019.
- 27 Sep 2019
- Prana, V.; Fayet, G.; Rotureau, P.; Adamo, C. Development of validated QSPR models for impact sensitivity of nitroaliphatic compounds. J. Hazard. Mater. 2012, 235-236, 169–177.
- 21 Feb 2019
- Oja, M.; Sild, S.; Maran, U. Logistic Classification Models for pH-Permeability Profile: Predicting Permeability Classes for the Biopharmaceutical Classification System. J. Chem. Inf. Model. 2019, 59, 2442-2455.
- 26 Jul 2018
- Käärik, M.; Maran, U.; Arulepp, M.; Perkson, A.; Leis, J. Quantitative nano-structure-property relationships for the nanoporous carbon: Predicting the performance of energy storage materials. ACS Appl. Energy Mater. 2018, 1, 4016-4024
Recent blog posts
On our mind
- 18 Oct 2019 | QsarDB archive parser in Python
Lisa Bang has developed a simple QsarDB archive parser for the Python programming language. This parser can be useful to someone interested in reproducing the QSAR provided in the QsarDB archive format.
- 30 Sep 2019 | QsarDB website got redesign
This summer, QsarDB’s main website underwent a major upgrade. The visual side was redesigned to have a modern look, but it was only a small part of the effort. Most of the work went into improving the documentation and its results are available in the new section, GUIDELINES.
- 31 Dec 2018 | Looking back to 2018
In year 2018 the third QsarDB workshop was held. The year culminated with the publication of a scientific article, which documented the "Best Practices for QSAR Model Reporting", which was also a summary of QsarDB team's experience in recent years on how QSAR models are documented in the scientific literature and also made suggestions for improving the current state-of-the-art.
- 31 Dec 2017 | Looking back to 2017
2017 was a year of normal technical development, QSAR models from 14 articles were digitalized and uploaded to the QsarDB repository, also the repository back-end was upgraded, etc.