CPANNatNIC software for counter-propagation neural network to assist in read-across
Viktor Drgan, Špela Župerl, Marjan Vračko, Claudia Ileana Cappelli, Marjana Novič · Journal of Cheminformatics · 2017
BACKGROUND: CPANNatNIC is software for development of counter-propagation artificial neural network models. Besides the interface for training of a new neural network it also provides an interface for visualisation of the results which was developed to aid in interpretation of the results and to use the program as a tool for read-across. RESULTS: The work presents the details of the program's interface. Parts of the interface are presented and how they can be used. The examples provided show how the user can build a new model and view the results of predictions using the interface. Examples are given to show how the software may be used in read-across. CONCLUSIONS: CPANNatNIC provides a simple user interface for model development and visualisation. The interface implements options which may simplify read-across procedure. Statistical results show better prediction accuracy of read-across predictions than model predictions where similar compounds could be identified, which indicates the importance of using read-across and usefulness of the program.