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Machine learning for electrocatalyst and photocatalyst design and discovery
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …
reducing the impact of global warming, and providing solutions to environmental pollution …
Artificial intelligence in drug discovery: recent advances and future perspectives
Introduction: Artificial intelligence (AI) has inspired computer-aided drug discovery. The
widespread adoption of machine learning, in particular deep learning, in multiple scientific …
widespread adoption of machine learning, in particular deep learning, in multiple scientific …
QSAR without borders
Prediction of chemical bioactivity and physical properties has been one of the most
important applications of statistical and more recently, machine learning and artificial …
important applications of statistical and more recently, machine learning and artificial …
Universal differential equations for scientific machine learning
In the context of science, the well-known adage" a picture is worth a thousand words" might
well be" a model is worth a thousand datasets." In this manuscript we introduce the SciML …
well be" a model is worth a thousand datasets." In this manuscript we introduce the SciML …
Automating drug discovery
Small-molecule drug discovery can be viewed as a challenging multidimensional problem in
which various characteristics of compounds—including efficacy, pharmacokinetics and …
which various characteristics of compounds—including efficacy, pharmacokinetics and …
Scoring functions for protein-ligand binding affinity prediction using structure-based deep learning: a review
The rapid and accurate in silico prediction of protein-ligand binding free energies or binding
affinities has the potential to transform drug discovery. In recent years, there has been a …
affinities has the potential to transform drug discovery. In recent years, there has been a …
MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm
Deep learning is an important branch of artificial intelligence that has been successfully
applied into medicine and two-dimensional ligand design. The three-dimensional (3D) …
applied into medicine and two-dimensional ligand design. The three-dimensional (3D) …
Simulation intelligence: Towards a new generation of scientific methods
The original" Seven Motifs" set forth a roadmap of essential methods for the field of scientific
computing, where a motif is an algorithmic method that captures a pattern of computation …
computing, where a motif is an algorithmic method that captures a pattern of computation …
Deep learning for drug design: an artificial intelligence paradigm for drug discovery in the big data era
Over the last decade, deep learning (DL) methods have been extremely successful and
widely used to develop artificial intelligence (AI) in almost every domain, especially after it …
widely used to develop artificial intelligence (AI) in almost every domain, especially after it …
Taking the leap between analytical chemistry and artificial intelligence: A tutorial review
The last 10 years have witnessed the growth of artificial intelligence into different research
areas, emerging as a vibrant discipline with the capacity to process large amounts of …
areas, emerging as a vibrant discipline with the capacity to process large amounts of …