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 …
Image-based profiling for drug discovery: due for a machine-learning upgrade?
SN Chandrasekaran, H Ceulemans, JD Boyd… - Nature Reviews Drug …, 2021 - nature.com
Image-based profiling is a maturing strategy by which the rich information present in
biological images is reduced to a multidimensional profile, a collection of extracted image …
biological images is reduced to a multidimensional profile, a collection of extracted image …
Best practices in machine learning for chemistry
Best practices in machine learning for chemistry | Nature Chemistry Skip to main content
Thank you for visiting nature.com. You are using a browser version with limited support for …
Thank you for visiting nature.com. You are using a browser version with limited support for …
Applications of machine learning in human microbiome studies: a review on feature selection, biomarker identification, disease prediction and treatment
LJ Marcos-Zambrano… - Frontiers in …, 2021 - frontiersin.org
The number of microbiome-related studies has notably increased the availability of data on
human microbiome composition and function. These studies provide the essential material …
human microbiome composition and function. These studies provide the essential material …
Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study
Rotating machinery intelligent diagnosis based on deep learning (DL) has gone through
tremendous progress, which can help reduce costly breakdowns. However, different …
tremendous progress, which can help reduce costly breakdowns. However, different …
Artificial intelligence in psychiatry research, diagnosis, and therapy
J Sun, QX Dong, SW Wang, YB Zheng, XX Liu… - Asian Journal of …, 2023 - Elsevier
Psychiatric disorders are now responsible for the largest proportion of the global burden of
disease, and even more challenges have been seen during the COVID-19 pandemic …
disease, and even more challenges have been seen during the COVID-19 pandemic …
Machine learning for metabolic engineering: A review
Abstract Machine learning provides researchers a unique opportunity to make metabolic
engineering more predictable. In this review, we offer an introduction to this discipline in …
engineering more predictable. In this review, we offer an introduction to this discipline in …
TransformerCPI: improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments
Motivation Identifying compound–protein interaction (CPI) is a crucial task in drug discovery
and chemogenomics studies, and proteins without three-dimensional structure account for a …
and chemogenomics studies, and proteins without three-dimensional structure account for a …
Machine learning-assisted low-dimensional electrocatalysts design for hydrogen evolution reaction
J Li, N Wu, J Zhang, HH Wu, K Pan, Y Wang, G Liu… - Nano-Micro Letters, 2023 - Springer
Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water.
Nevertheless, the conventional" trial and error" method for producing advanced …
Nevertheless, the conventional" trial and error" method for producing advanced …
Multiscale modeling meets machine learning: What can we learn?
GCY Peng, M Alber, A Buganza Tepole… - … Methods in Engineering, 2021 - Springer
Abstract Machine learning is increasingly recognized as a promising technology in the
biological, biomedical, and behavioral sciences. There can be no argument that this …
biological, biomedical, and behavioral sciences. There can be no argument that this …