Graph neural networks for materials science and chemistry
Abstract Machine learning plays an increasingly important role in many areas of chemistry
and materials science, being used to predict materials properties, accelerate simulations …
and materials science, being used to predict materials properties, accelerate simulations …
[HTML][HTML] Artificial intelligence in pharmaceutical technology and drug delivery design
Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic
knowledge and provides expedited solutions to complex challenges. Remarkable …
knowledge and provides expedited solutions to complex challenges. Remarkable …
Amelioration of Alzheimer's disease pathology by mitophagy inducers identified via machine learning and a cross-species workflow
A reduced removal of dysfunctional mitochondria is common to aging and age-related
neurodegenerative pathologies such as Alzheimer's disease (AD). Strategies for treating …
neurodegenerative pathologies such as Alzheimer's disease (AD). Strategies for treating …
Deep learning for drug repurposing: Methods, databases, and applications
Drug development is time‐consuming and expensive. Repurposing existing drugs for new
therapies is an attractive solution that accelerates drug development at reduced …
therapies is an attractive solution that accelerates drug development at reduced …
Artificial intelligence in the battle against coronavirus (COVID-19): a survey and future research directions
Artificial intelligence (AI) has been applied widely in our daily lives in a variety of ways with
numerous success stories. AI has also contributed to dealing with the coronavirus disease …
numerous success stories. AI has also contributed to dealing with the coronavirus disease …
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 …
GeneCompass: deciphering universal gene regulatory mechanisms with a knowledge-informed cross-species foundation model
Deciphering universal gene regulatory mechanisms in diverse organisms holds great
potential for advancing our knowledge of fundamental life processes and facilitating clinical …
potential for advancing our knowledge of fundamental life processes and facilitating clinical …
Natural language processing for smart healthcare
Smart healthcare has achieved significant progress in recent years. Emerging artificial
intelligence (AI) technologies enable various smart applications across various healthcare …
intelligence (AI) technologies enable various smart applications across various healthcare …
[HTML][HTML] A comprehensive review of artificial intelligence and network based approaches to drug repurposing in Covid-19
Conventional drug discovery and development is tedious and time-taking process; because
of which it has failed to keep the required pace to mitigate threats and cater demands of viral …
of which it has failed to keep the required pace to mitigate threats and cater demands of viral …
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery--A Focus on Affinity Prediction Problems with Noise Annotations
AI-aided drug discovery (AIDD) is gaining increasing popularity due to its promise of making
the search for new pharmaceuticals quicker, cheaper and more efficient. In spite of its …
the search for new pharmaceuticals quicker, cheaper and more efficient. In spite of its …