Results 71 to 80 of about 8,038,825 (297)

Visual evaluation of graph representation learning based on the presentation of community structures

Visual Informatics
Various graph representation learning models convert graph nodes into vectors using techniques like matrix factorization, random walk, and deep learning. However, choosing the right method for different tasks can be challenging.
Yong Zhang, Lihong Cai, Yuhua Liu, Yize Li, Songyue Li, Yuming Ma, Yuwei Meng, Zhiguang Zhou   +7 more
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

Spatial and single‐nuclei transcriptomics reveals idiosyncratic and generic patterns in papillary and anaplastic thyroid cancers

Molecular Oncology, EarlyView.
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur, Joel Rodrigues Vitória, Manuel Saiselet, Ligia Craciun, Denis Larsimont, Anne Lefort, Frédérick Libert, Carine Maenhaut, Sabine Costagliola, Maxime Tarabichi, Mirian Romitti, Vincent Detours   +11 more
wiley   +1 more source

Single‐cell DNA methylation profiling: Technologies, computation, and applications in precision oncology

Molecular Oncology, EarlyView.
Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley   +1 more source

WMGCN: Weighted Meta-Graph Based Graph Convolutional Networks for Representation Learning in Heterogeneous Networks

IEEE Access, 2020
Network embedding has been an effective tool to analyze heterogeneous networks (HNs) by representing nodes in a low-dimensional space. Although many recent methods have been proposed for representation learning of HNs, there is still much room for ...
Jinli Zhang, Zongli Jiang, Zheng Chen, Xiaohua Hu   +3 more
doaj   +1 more source

CEACAM1 participation in breast cancer progression

Molecular Oncology, EarlyView.
In invasive breast cancer (BC), CEACAM1 shifts from an apical to a uniform membranous/cytoplasmic pattern, or is lost, as tumors dedifferentiate, inversely tracking the Ki‐67 proliferative index. In MCF‐7 cells, only CEACAM1‐4L suppresses proliferation, repressing cell cycle and growth factor genes.
Mykola Lyndin, Irina Kube‐Golovin, Anatolii Romaniuk, Gunther Wennemuth   +3 more
wiley   +1 more source

Signed Graph Representation Learning

, 2023
This thesis considers the research on signed graph representation learning in different aspects. Signed graphs model complex relations using both positive and negative edges and signed graph neural networks (SGNNs) are powerful tools to analyze signed ...
Zhang, Zeyu
core  

Deep Lagrangian Propagation in Graph Neural Networks [PDF]

, 2020
Graph Neural Networks (Scarselli et al., 2009) exploit an iterative diffusion procedure to compute the node states as the fixed point of the trainable state transition function. In this paper, we show how to cast this scheme as a constrained optimization
Marco Maggini, Stefano Melacci, Matteo Tiezzi, Giuseppe Marra   +3 more
core   +1 more source

Partial FAK suppression promotes tumor growth, an effect reversed by macrophage p110δ PI3K inactivation

Molecular Oncology, EarlyView.
Partial inhibition of focal adhesion kinase (FAK) can paradoxically promote tumor growth, rather than simply producing a weaker antitumor effect than that observed with strong FAK suppression. In breast cancer and melanoma models, targeting p110δ PI3K, particularly in macrophages, counteracted these tumor‐promoting effects, highlighting the importance ...
Lydia Xenou, Niki Tzenaki, Anna Tsapara, Maria Tzardi, Evangelia A. Papakonstanti   +4 more
wiley   +1 more source

Reliable Knowledge Graph Path Representation Learning

IEEE Access, 2020
Knowledge graphs, which have been widely utilized in various intelligent applications, are highly incomplete. Many valid facts can be inferred from existing facts in knowledge graphs. A promising approach for this task is a knowledge graph representation
Seungmin Seo, Byungkook Oh, Kyong-Ho Lee
doaj   +1 more source