With the popularity of knowledge graphs growing rapidly, large amounts of RDF graphs have
been released, which raises the need for addressing the challenge of distributed subgraph …

With RDF becoming the de facto standard for representing knowledge graphs, it is
indispensable to develop scalable subgraph matching algorithms over big RDF graphs stored in …

Linked Data, a method to publish interrelated data on the Semantic Web, has rapidly developed
in recent years due to new techniques which enhance the availability of knowledge. As …

With the proliferation of knowledge graphs, large amounts of RDF graphs have been released,
which raises the need for addressing the challenge of distributed SPARQL queries. In this …

Abstract Knowledge Representation Learning (KRL) has been playing an essential role in
many AI applications and achieved desirable results for some downstream tasks. However, …

The dearth of technologies that allow gene modulation and therapy with high spatiotemporal
precision remains a bottleneck in biomedical research and applications. Here we present a …

Abstract Knowledge Representation Learning (KRL) methods produce unsupervised node
features from knowledge graphs that can be used for a variety of machine learning tasks. …

Design of biosensors capable of imaging ATP and glutathione (GSH) in mitochondria remains
a challenge, despite their importance in elucidating their correlated pathophysiological …

Soil is an essential source of nutrients for crop growth, but excessive chemical fertilizer can
lead to soil acidification and decreased sustainability. Organic fertilizer helps improve soil …

Keloids are fibroproliferative disorders characterized by the overabundant deposition of
extracellular matrix (ECM), especially collagen and overgrowth of scar tissue in response to …