Multiple recent works, in the context of cancer and COVID-19 drug discovery, have used joint tensor decompositions to suggest drug repositioning candidates.
Tensors and their decomposition provide an ideal framework for formulating and solving drug repositioning problems because known relationships are easily ...
Predicting associations among drugs, targets and diseases by tensor decomposition for drug repositioning · Medicine, Computer Science. BMC Bioinformatics · 2019.
We find 10/31 in-trial drugs in top-100 predictions in our approach which is remarkable compared to most of state-of-art aligned approaches which also rely on ...
Jul 21, 2022 · Tensor decomposition enables us to integrate multiple drug- and disease-related data to boost the performance of prediction. In this study, a ...
People also ask
What are the techniques of drug repositioning?
What are the stages of drug repurposing?
What is the drug repositioning business model?
What is the meaning of drug repositioning?
Jul 21, 2022 · In this study, a nonnegative tensor decomposition for drug repositioning, NTD-DR, is proposed. In order to capture the hidden information in drug-target, drug- ...
Jun 27, 2024 · Drug repurposing allows drug discovery to consider reusing approved compounds to mitigate those issues. The outcomes of past clinical trials can ...
For example, in the work of detecting repositioning drugs [10], we created a three-dimensional dataset that measures the co-mention of disease, drug, and ...
Predicting associations among drugs, targets and diseases by tensor decomposition for drug repositioning. BMC Bioinformatics, 20 (2019), p. 628. View in ...
Jul 15, 2020 · In this paper, we present a novel approach called iDrug, which seamlessly integrates drug repositioning and drug-target prediction into one coherent model via ...