Major depressive disorder

W Marx, BWJH Penninx, M Solmi… - Nature Reviews …, 2023 - nature.com
Major depressive disorder (MDD) is characterized by persistent depressed mood, loss of
interest or pleasure in previously enjoyable activities, recurrent thoughts of death, and …

Drug repurposing for cancer therapy

Y ** personalized diagnostic strategies and targeted treatments requires a deep
understanding of disease biology and the ability to dissect the relationship between …

Graph neural networks: foundation, frontiers and applications

L Wu, P Cui, J Pei, L Zhao, X Guo - … of the 28th ACM SIGKDD conference …, 2022 - dl.acm.org
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

[HTML][HTML] Revolutionizing medicinal chemistry: the application of artificial intelligence (AI) in early drug discovery

R Han, H Yoon, G Kim, H Lee, Y Lee - Pharmaceuticals, 2023 - mdpi.com
Artificial intelligence (AI) has permeated various sectors, including the pharmaceutical
industry and research, where it has been utilized to efficiently identify new chemical entities …

Pre-training molecular graph representation with 3d geometry

S Liu, H Wang, W Liu, J Lasenby, H Guo… - arxiv preprint arxiv …, 2021 - arxiv.org
Molecular graph representation learning is a fundamental problem in modern drug and
material discovery. Molecular graphs are typically modeled by their 2D topological …

Geometry-enhanced molecular representation learning for property prediction

X Fang, L Liu, J Lei, D He, S Zhang, J Zhou… - Nature Machine …, 2022 - nature.com
Effective molecular representation learning is of great importance to facilitate molecular
property prediction. Recent advances for molecular representation learning have shown …