SUMMARY: Deep learning (DL) can significantly accelerate virtual screening of ultra-large chemical libraries, enabling the evaluation of billions of compounds at a fraction of the computational cost and time required by conventional docking. Here, we...
Recently, machine learning methods have been developed to identify various peptide bio-activities. However, due to the lack of experimentally validated peptides, machine learning methods cannot provide a sufficiently trained model, easily resulting i...
MOTIVATION: The rapid growth in literature accumulates diverse and yet comprehensive biomedical knowledge hidden to be mined such as drug interactions. However, it is difficult to extract the heterogeneous knowledge to retrieve or even discover the l...
The side effects of drugs present growing concern attention in the healthcare system. Accurately identifying the side effects of drugs is very important for drug development and risk assessment. Some computational models have been developed to predic...
One of the main problems with the joint use of multiple drugs is that it may cause adverse drug interactions and side effects that damage the body. Therefore, it is important to predict potential drug interactions. However, most of the available pred...
For an increasing number of preclinical samples, both detailed molecular profiles and their responses to various drugs are becoming available. Efforts to understand, and predict, drug responses in a data-driven manner have led to a proliferation of m...
Coronavirus disease 2019 (COVID-19) has impacted public health as well as societal and economic well-being. In the last two decades, various prediction algorithms and tools have been developed for predicting antiviral peptides (AVPs). The current COV...
MOTIVATION: Drug combination therapy has become an increasingly promising method in the treatment of cancer. However, the number of possible drug combinations is so huge that it is hard to screen synergistic drug combinations through wet-lab experime...
Long non-coding RNAs (lncRNAs) are a class of RNA molecules with more than 200 nucleotides. A growing amount of evidence reveals that subcellular localization of lncRNAs can provide valuable insights into their biological functions. Existing computat...
Studies in health technology and informatics
Jan 14, 2022
BACKGROUND: Artificial Intelligence (AI) has seen an increased application within digital healthcare interventions (DHIs). DHIs use entails challenges about their safety assurance. Exacerbated by regulatory requirements, in the UK, this places the on...
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