Results 71 to 80 of about 468,662 (346)
Following high dose rate brachytherapy (HDR‐BT) for hepatocellular carcinoma (HCC), patients were classified as responders and nonresponders. Post‐therapy serum induced increased BrdU incorporation and Cyclin E expression of Huh7 and HepG2 cells in nonresponders, but decreased levels in responders.
Lukas Salvermoser +14 more
wiley +1 more source
Temporal Knowledge Graph Completion using a Linear Temporal Regularizer and Multivector Embeddings
Representation learning approaches for knowledge graphs have been mostly designed for static data. However, many knowledge graphs involve evolving data, e.g., the fact (The President of the United States is Barack Obama) is valid only from 2009 to 2017 ...
Chengjin Xu +3 more
semanticscholar +1 more source
KBGAN: Adversarial Learning for Knowledge Graph Embeddings
We introduce KBGAN, an adversarial learning framework to improve the performances of a wide range of existing knowledge graph embedding models. Because knowledge graphs typically only contain positive facts, sampling useful negative training examples is ...
Cai, Liwei, Wang, William Yang
core +1 more source
Survivin and Aurora Kinase A control cell fate decisions during mitosis
Aurora A interacts with survivin during mitosis and regulates its centromeric role. Loss of Aurora A activity mislocalises survivin, the CPC and BubR1, leading to disruption of the spindle checkpoint and triggering premature mitotic exit, which we refer to as ‘mitotic slippage’.
Hana Abdelkabir +2 more
wiley +1 more source
Few-shot temporal knowledge graph completion based on meta-optimization
Knowledge Graphs (KGs) have become an increasingly important part of artificial intelligence, and KGs have been widely used in artificial intelligence fields such as intelligent answering questions and personalized recommendation.
Lin Zhu +3 more
doaj +1 more source
APKGC: Noise-enhanced Multi-Modal Knowledge Graph Completion with Attention Penalty
Multimodal knowledge graphs (MMKG) store structured world knowledge enriched with multimodal descriptive information. However, MMKG often faces the challenge of incompleteness.
Yue Jian +6 more
semanticscholar +1 more source
Knowledge graph completion for scholarly knowledge graph
Scholarly knowledge graph is a knowledge graph that is used to represent knowledge contained in scientific publication documents. The information we can find in a scientific publication document is as follows: author, institution, name of journal/conference, and research topic. A knowledge graph that has been built is usually still not perfect.
Taufiqurrahman Taufiqurrahman +2 more
openaire +1 more source
Automatic Inference of Graph Transformation Rules Using the Cyclic Nature of Chemical Reactions
Graph transformation systems have the potential to be realistic models of chemistry, provided a comprehensive collection of reaction rules can be extracted from the body of chemical knowledge. A first key step for rule learning is the computation of atom-
Flamm, Christoph +3 more
core +1 more source
Liquid biopsy epigenetics: establishing a molecular profile based on cell‐free DNA
Cell‐free DNA (cfDNA) fragments in plasma from cancer patients carry epigenetic signatures reflecting their cells of origin. These epigenetic features include DNA methylation, nucleosome modifications, and variations in fragmentation. This review describes the biological properties of each feature and explores optimal strategies for harnessing cfDNA ...
Christoffer Trier Maansson +2 more
wiley +1 more source
Knowledge Graph Completion With Pattern-Based Methods
Knowledge graphs (KGs) are popularly used to develop several intelligent applications. Revealing valuable knowledge hidden in these graphs opened up a branch of research, known as KG reasoning, aiming at predicting the missing links.
Maryam Sabet +2 more
doaj +1 more source

