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Published in 2022 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.2c00485
Abstract: Protein-ligand scoring functions are widely used in structure-based drug design for fast evaluation of protein-ligand interactions, and it is of strong interest to develop scoring functions with machine-learning approaches. In this work, by expanding the…
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Keywords:
scoring ranking;
ligand scoring;
scoring functions;
machine learning ... See more keywords
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2
Published in 2022 at "ACS Omega"
DOI: 10.1021/acsomega.2c01723
Abstract: Prediction of protein–ligand binding affinities is a central issue in structure-based computer-aided drug design. In recent years, much effort has been devoted to the prediction of the binding affinity in protein–ligand complexes using machine learning…
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Keywords:
scoring ranking;
xlpfe;
machine learning;
protein ligand ... See more keywords
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0
Published in 2020 at "Scientific Reports"
DOI: 10.1038/s41598-020-66611-8
Abstract: Only few applications are currently dealing with personalized adverse drug reactions (ADRs) prediction in case of polypharmacy. The study aimed to develop a patient-tailored ADR web application, considering characteristics from 734 drugs and relevant patient…
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Keywords:
patient tailored;
severity;
scoring ranking;
adverse drug ... See more keywords
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Published in 2024 at "Natural Hazards and Earth System Sciences"
DOI: 10.5194/nhess-24-1401-2024
Abstract: Abstract. A probabilistic seismic hazard model consists of a set of weighted models/branches that describes the center, the body and the range of seismic hazard. Owing to the intrinsic nature of this kind of analysis,…
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Keywords:
hazard;
intensity;
probabilistic seismic;
model ... See more keywords