Pred-Skin app is based on statistically significant and externally predictive QSAR models of skin sensitization. The models were built using largest database containing human and LLNA data. So far, it is the only tool available for predicting skin sensitization based on human data!
Developed as tool for indentify putative skin sensitizers. The Consensus models were generated averaging the predictions of individual models, achieving balanced accuracy, sensitivity, and specificity up to 0.70-0.84 with the coverage of 0.65-1.
The probability maps allow the visualization of predicted fragment contribution. This method provides an easy interpretation of the predicted activity, allowing the user to easilly propose structural modifications.
Click the right button on the whiteboard of the "Molecular Editor" and select "Paste MOL or SDF or SMILES"." SDF and MOL files are accepted.
Bulk prediction is useful when you want to generate predictions for a large set of compounds all at once, and then a link containing the results report will be available for download. Also, a copy of this report will be sent by email. Our system allows the evaluation of up to 10,000 compounds at once with low latency.
Pred-Skin employs machine learning models based on human and local lymph node assay (LLNA) skin sensitization information to help end users to "make right decisions faster."
A user-friendly interface that integrates smoothly executing functions within the application.