Artificial intelligence, deep convolutional neural networks, and deep learning are all niche
terms that are increasingly appearing in scientific presentations as well as in the general …

Background There is a need for software applications that provide users with a complete
and extensible toolkit for chemo- and bioinformatics accessible from a single workbench. …

The quantification and identification of cellular phenotypes from high-content microscopy
images has proven to be very useful for understanding biological activity in response to …

Background The Chemistry Development Kit (CDK) is a widely used open source cheminformatics
toolkit, providing data structures to represent chemical concepts along with methods …

Background Making data available as Linked Data using Resource Description Framework (RDF)
promotes integration with other web resources. RDF documents can natively link to …

The reproducibility of experiments has been a long standing impediment for further scientific
progress. Computational methods have been instrumental in drug discovery efforts owing to …

One of the challenges with predictive modeling is how to quantify the reliability of the models’
predictions on new objects. In this work we give an introduction to conformal prediction, a …

Mitochondrial toxicity is an important safety endpoint in drug discovery. Models based solely
on chemical structure for predicting mitochondrial toxicity are currently limited in accuracy …

Unreliable predictions can occur when an artificial intelligence (AI) system is presented with
data it has not been exposed to during training. We demonstrate the use of conformal …

Background The Blue Obelisk movement was established in 2005 as a response to the lack
of Open Data, Open Standards and Open Source (ODOSOS) in chemistry. It aims to make it …