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Article
Open AccessArtificial intelligence to guide precision anticancer therapy with multitargeted kinase inhibitors
Vast amounts of rapidly accumulating biological data related to cancer and a remarkable progress in the field of artificial intelligence (AI) have paved the way for precision oncology. Our recent contribution ...
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Article
Open AccessAn integrated network representation of multiple cancer-specific data for graph-based machine learning
Genomic profiles of cancer cells provide valuable information on genetic alterations in cancer. Several recent studies employed these data to predict the response of cancer cell lines to drug treatment. Noneth...
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Article
Open AccessGraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data
Traditional techniques to identify macromolecular targets for drugs utilize solely the information on a query drug and a putative target. Nonetheless, the mechanisms of action of many drugs depend not only on...
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Article
Open AccesseToxPred: a machine learning-based approach to estimate the toxicity of drug candidates
The efficiency of drug development defined as a number of successfully launched new pharmaceuticals normalized by financial investments has significantly declined. Nonetheless, recent advances in high-throughp...
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Article
Novel tailoring algorithm for abrupt motion artifact removal in photoplethysmogram signals
Photoplethysmogram (PPG) signals are widely used for wearable electronic devices nowadays. The PPG signal is extremely sensitive to the motion artifacts (MAs) caused by the subject’s movement. The detection an...
