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Published in 2018 at "Methods in molecular biology"
DOI: 10.1007/978-1-4939-8639-2_12
Abstract: Identification of drug-target interactions is a crucial process in drug discovery. In this chapter, we present protocols for recent advancements in machine learning methods for predicting drug-target interactions from heterogeneous biological data in a chemogenomic…
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Keywords:
kernel;
target;
methods predicting;
drug ... See more keywords
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Published in 2019 at "Methods in molecular biology"
DOI: 10.1007/978-1-4939-8955-3_14
Abstract: Therapeutic effects of drugs are mediated via interactions between them and their intended targets. As such, prediction of drug-target interactions is of great importance. Drug-target interaction prediction is especially relevant in the case of drug…
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Keywords:
drug;
prediction drug;
drug target;
target interactions ... See more keywords
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Published in 2020 at "Trends in pharmacological sciences"
DOI: 10.1016/j.tips.2020.03.001
Abstract: Recently, Perrin et al. reported the application of thermal proteome profiling (TPP), a cellular thermal shift assay with an unbiased proteomics readout to complex tissue samples from model organisms and patient-derived whole blood. This study…
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Keywords:
characterizing drug;
drug;
drug target;
interactions shifting ... See more keywords
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Published in 2018 at "Genomics"
DOI: 10.1016/j.ygeno.2018.12.007
Abstract: The identification of drug-target interactions has great significance for pharmaceutical scientific research. Since traditional experimental methods identifying drug-target interactions is costly and time-consuming, the use of machine learning methods to predict potential drug-target interactions has…
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Keywords:
target;
drug;
drug target;
target interactions ... See more keywords
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Published in 2022 at "ACS Omega"
DOI: 10.1021/acsomega.2c00424
Abstract: In silico methods to identify novel drug–target interactions (DTIs) have gained significant importance over conventional techniques owing to their labor-intensive and low-throughput nature. Here, we present a machine learning-based multiclass classification workflow that segregates interactions…
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Keywords:
neural network;
target interactions;
drug target;
deep neural ... See more keywords
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Published in 2017 at "Scientific Reports"
DOI: 10.1038/srep41206
Abstract: The alarming increase of pathogenic bacteria that are resistant to multiple antibiotics is now recognized as a major health issue fuelling demand for new drugs. Bacterial resistance is often caused by molecular changes at the…
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Keywords:
surface;
drug;
drug resistant;
drug target ... See more keywords
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Published in 2022 at "Proceedings of the National Academy of Sciences of the United States of America"
DOI: 10.1073/pnas.2114064119
Abstract: Significance Plant nonhost resistance (NHR) prevents infection by all members of most microbial species, but its molecular mechanisms are not well understood. We found that effector proteins from the potato blight pathogen Phytophthora infestans, which…
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Keywords:
target interactions;
exploiting breakdown;
effector target;
effector ... See more keywords
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Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbab582
Abstract: Targeted drugs have been applied to the treatment of cancer on a large scale, and some patients have certain therapeutic effects. It is a time-consuming task to detect drug-target interactions (DTIs) through biochemical experiments. At…
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Keywords:
matrix;
target interactions;
drug target;
multiple kernel ... See more keywords
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Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btac485
Abstract: MOTIVATION Identifying drug-target interactions is a crucial step for drug discovery and design. Traditional biochemical experiments are credible to accurately validate drug-target interactions. However, they are also extremely laborious, time-consuming, and expensive. With the collection…
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Keywords:
target interactions;
independent features;
drug target;
attention ... See more keywords
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Published in 2018 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btx731
Abstract: Abstract Motivation Finding computationally drug–target interactions (DTIs) is a convenient strategy to identify new DTIs at low cost with reasonable accuracy. However, the current DTI prediction methods suffer the high false positive prediction rate. Results…
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Keywords:
method;
graph;
drug target;
target interactions ... See more keywords
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Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3026479
Abstract: Predicting the target-drug interactions (DITs) is of great important for screening new drug candidate and understanding biological processes. However, identifying the drug-target interactions through traditional experiments is still costly, laborious and complicated. Thus, there is…
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Keywords:
drug;
method;
target interactions;
drug target ... See more keywords