Results 101 to 110 of about 1,708,308 (346)

A Graph-Convolutional Neural Network for Addressing Small-Scale Reaction Prediction

, 2021
We describe a graph-convolutional neural network (GCN) model whose reaction prediction capable as potent as the transformer model on sufficient data, and adopt the Baeyer-Villiger oxidation to explore their performance differences on limited data.
Yejian, Wu, Hongliang, Duan, Chengyun, Zhang, Ling, Wang   +3 more
core   +1 more source

Deciphering transcriptional plasticity in pancreatic ductal adenocarcinoma reveals alterations in sensory neuron innervation

Molecular Oncology, EarlyView.
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova, Michele Montrone, Uday Rangaswamy, Francesco Diversi, Irene Schiavo, Denise Ferrarini, Roberta Di Florio, Irene Longo, Michele Coscia, Nicola Zamboni, Giorgia Demontis, Lisa Veghini, Vincenzo Corbo, Remo Sanges, Paul Heppenstall   +14 more
wiley   +1 more source

A Graph Neural Network Assisted Monte Carlo Tree Search Approach to Traveling Salesman Problem

IEEE Access, 2020
We tackle the classical traveling salesman problem (TSP) by combining a graph neural network and Monte Carlo Tree Search. We adopt a greedy algorithm framework to derive a promising tour by adding the vertices successively.
Zhihao Xing, Shikui Tu
doaj   +1 more source

Metastasis on pause: How dormant tumor cells stay hidden within the tumor microenvironment and evade immune surveillance

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, Jose Javier Bravo‐Cordero   +1 more
wiley   +1 more source

Review of Graph Neural Networks [PDF]

Jisuanji kexue
With the rapid development of artificial intelligence,deep learning has achieved great success in data that can be represented in Euclidean spaces,such as images,text,and speech.However,it has been difficult to apply deep learning to non-Eucli-dean ...
HOU Lei, LIU Jinhuan, YU Xu, DU Junwei
doaj   +1 more source

Epigenetic heterogeneity and plasticity in therapy‐induced tumor states through single‐cell multi‐omics

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, Hwiyeong Lee, Jin Hong, Daechan Park   +3 more
wiley   +1 more source

Graph transformer neural network for chemical reactivity prediction

, 2023
Optimizing the properties of advanced drug candidates can be facilitated by directly introducing certain chemical groups without having to synthesize the molecules from scratch.
David B., Konrad, Uwe, Grether, David F., Nippa, Gisbert, Schneider, Jens, Wolfard, Oliver, Scheidegger, Rainer E., Martin, Alex T., Müller, Clemens, Isert, Kenneth, Atz, Martin, Binder   +10 more
core   +1 more source

Loss of AMBRA1 activates MAPK and angiogenesis signaling pathways in melanoma cells

FEBS Open Bio, EarlyView.
Loss of AMBRA1 in melanoma cells activates multiple oncogenic pathways associated with tumor progression. Transcriptomic and protein network analyses revealed that AMBRA1 depletion enhances MAPK/ERK signaling, angiogenesis, TGF‐β/EMT signaling, and Wnt/axon guidance pathways.
Milad Ibrahim, Marco Corazzari, Iman Osman, Jane Armstrong, Noel Carter   +4 more
wiley   +1 more source

Improving data security with the utilization of matrix columnar transposition techniques [PDF]

E3S Web of Conferences
The Graph Neural Network (GNN) is an advanced use of graph theory that is used to address complex network problems. The application of Graph Neural Networks allows the development of a network by the modification of weights associated with the vertices ...
Tulus, Sy Syafrizal, Sugeng Kiki A., Simanjuntak Rinovia, Marpaung J.L.   +4 more
doaj   +1 more source

From energy provision to protein synthesis: Tunnelling nanotubes as mediators of intercellular metabolic cooperation in cancer

FEBS Open Bio, EarlyView.
The cytoskeleton‐mediated transport of mitochondria via tunnelling nanotubes restores respiration, increases ATP production, rescues cells from apoptosis, activates the AKT/mTOR signalling pathway, promotes cell migration and invasiveness, contributes to cancer progression and treatment resistance.
Stanislava Martínková, Jan Trnka
wiley   +1 more source