Results 71 to 80 of about 4,082,283 (306)
Emerging experimental and computational methods for studying redox‐regulated structural transitions
FEBS Letters, EarlyView.Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
Translophagy—A potential link between autophagy impairment and translational errors
FEBS Letters, EarlyView.Neurodegenerative diseases are characterised by the accumulation of abnormal proteins and protein aggregates, but their origin often remains unknown. We propose that selective autophagy removes damaged protein‐making machinery, preventing errors during protein synthesis.
Mykola V. Korolchuk +11 more
wiley +1 more source
Clenshaw Graph Neural Networks
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023 Graph Convolutional Networks (GCNs), which use a message-passing paradigm with stacked convolution layers, are foundational methods for learning graph representations. Recent GCN models use various residual connection techniques to alleviate the model degradation problem such as over-smoothing and gradient vanishing.
Yuhe Guo, Zhewei Wei
openaire +4 more sources
Degree-Aware Graph Neural Network Quantization
Entropy, 2023 In this paper, we investigate the problem of graph neural network quantization. Despite the great success on convolutional neural networks, directly applying current network quantization approaches to graph neural networks faces two challenges.
Ziqin Fan, Xi Jin
doaj +1 more source
Deep recurrent graph neural networks [PDF]
, 2020 Graph Neural Networks (GNN) show good results in classification and regression on graphs, notwithstanding most GNN models use a limited depth. In fact, they are composed of only a few stacked graph convolutional layers.
Pasa L., Sperduti A., Navarin N.
core
Prospecting the protein design landscape
FEBS Letters, EarlyView.This review outlines the current state of various protein design approaches. We discuss the current possibilities enabled by recently released tools, highlight future avenues to pursue in protein design, and underscore the crucial role of key databases and resources for successful protein design workflows.
Jakob R. Riccabona +4 more
wiley +1 more source
Proceedings of the AAAI Conference on Artificial Intelligence, 2022 Graph Neural Networks (GNNs) have shown advantages in various graph-based applications. Most existing GNNs assume strong homophily of graph structure and apply permutation-invariant local aggregation of neighbors to learn a representation for each node. However, they fail to generalize to heterophilic graphs, where most neighboring nodes have different
Tianmeng Yang +5 more
openaire +3 more sources
Molecular Oncology, EarlyView.Dormant cancer cells can hide in distant organs for years, evading treatment and the immune system. This review highlights how signals from the surrounding tissue and immune environment keep these cells inactive or trigger their reawakening. Understanding these mechanisms may help develop therapies to eliminate or control dormant cells and prevent ...
Kanishka Tiwary +1 more
wiley +1 more source
Approach to the fake news detection using the graph neural networks
Journal of Edge Computing, 2023 The experience of Russia’s war against Ukraine demonstrates the relevance and necessity of understanding the problems of constant disinformation, the spread of propaganda, and the implementation of destructive negative psychological influence. The issue
Ihor A. Pilkevych +3 more
doaj +1 more source
Molecular Oncology, EarlyView.Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim +3 more
wiley +1 more source