Myrto F Mavilidi, Caterina Pesce, Emiliano Mazzoli, Sue Bennett, Fred Paas, Anthony D Okely, Steven J Howard
Effects of Cognitively Engaging Physical Activity on Preschool Children's Cognitive Outcomes
Research quarterly for exercise and sport
recent years alternative animal testing methods computational machine learning approaches become increasingly crucial toxicity testing however complexity scarcity available biomedical data challenge development predictive models combining nonlinear machine learning together multicondition descriptors offers solution using data various assays create robust model work applies multicondition descriptors mcds develop qstr quantitative structuretoxicity relationship model based large toxicity data set comprising 80000 compounds 59 different end points 122572 data points prediction capabilities developed singletask multiend point machine learning models well novel data analysis approach use convolutional neural networks cnn discussed results show using mcds significantly improves model using cnn1d yields best result r2train 093 r2ext 070 several structural features showed high level contribution toxicity including van der waals surface area vsa number nitrogencontaining fragments nn presence sp fragments ionization potential presence cn fragments developed models useful tools predict toxicity various compounds different conditions enabling quick toxicity assessment new compounds