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.
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.
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.
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.
Besides other activities, like the second QsarDB workshop, 2016 was an interesting year when, at the beginning of the year, in February, collaboration with Taylor & Francis reached to the point where QSAR models published in their journal articles can be automatically linked with the QsarDB repository.