Results 161 to 170 of about 30,563 (303)
Knowledge graph embedding for profiling the interaction between transcription factors and their target genes. [PDF]
Wu YH +7 more
europepmc +1 more source
This study identifies that methylglyoxal may play an important role in heart‐brain interactions after myocardial infarction. Myocardial infarction leads to increased levels of methylglyoxal‐derived advanced glycation end‐products (MG‐H1) in the brain of mice, which is associated with loss of blood‐brain barrier integrity and neuroinflammation ...
Ramis Ileri, Xixi Guo, Erik J. Suuronen
wiley +1 more source
Predicting protein and pathway associations for understudied dark kinases using pattern-constrained knowledge graph embedding. [PDF]
Salcedo MV +5 more
europepmc +1 more source
We developed a nanoparticle named OAF, which simultaneously targeted to both the brain and liver via the transferrin receptor 1 (TfR1) receptor, promoting lipoprotein receptor‐related protein 1 (LRP1) expression to enhance amyloid‐beta (Aβ) clearance. In AD mice model, OAF significantly reduced Aβ deposition and cognitive impairment, while a mitigating
Wenshuai Gong +8 more
wiley +1 more source
Combining the External Medical Knowledge Graph Embedding to Improve the Performance of Syndrome Differentiation Model. [PDF]
Ye Q, Yang R, Cheng CL, Peng L, Lan Y.
europepmc +1 more source
In ovarian cancer, MEOX1 activates the SPHK1/S1P pathway to promote both tumor progression and tumor–stroma crosstalk. MEOX1‐dependent signaling drives CAF activation, enhances VEGF‐C expression, and stimulates lymphangiogenesis, ultimately facilitating lymph node metastasis.
Jiajia Li +10 more
wiley +1 more source
The current static detection method of network source code vulnerabilities mainly relies on the static analysis of binary code. However, due to the failure to fully simulate the actual operating environment of programs, some vulnerabilities that trigger ...
Peng Xiao +3 more
doaj +1 more source
Ensembles of knowledge graph embedding models improve predictions for drug discovery. [PDF]
Rivas-Barragan D +3 more
europepmc +1 more source
Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu +5 more
wiley +1 more source
Molecular-evaluated and explainable drug repurposing for COVID-19 using ensemble knowledge graph embedding. [PDF]
Islam MK +5 more
europepmc +1 more source

