Results 51 to 60 of about 318,242 (266)
Embedding Uncertain Temporal Knowledge Graphs
Knowledge graph (KG) embedding for predicting missing relation facts in incomplete knowledge graphs (KGs) has been widely explored. In addition to the benchmark triple structural information such as head entities, tail entities, and the relations between
Tongxin Li +5 more
doaj +1 more source
This study reveals that the small GTPase Rab14 is necessary for human papillomavirus (HPV) infection and plays an essential role in the transport of virions to the trans‐Golgi network (TGN). HPV in the early endosome (EE), which harbors GTP‐bound Rab14, is transported to the TGN through the switch of Rab14 from its GTP‐bound to GDP‐bound form.
Yoshiyuki Ishii, Iwao Kukimoto
wiley +1 more source
We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Graph Attention Networks With Local Structure Awareness for Knowledge Graph Completion
Graph neural networks have been proven to be very effective for representation learning of knowledge graphs. Recent methods such as SACN and CompGCN, have achieved the most advanced results in knowledge graph completion.
Kexi Ji, Bei Hui, Guangchun Luo
doaj +1 more source
From mice to humans—divergent strategies for intestinal homeostasis and regeneration
Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa +2 more
wiley +1 more source
Research on Service Discovery Methods Based on Knowledge Graph
Service discovery is one of the main goals of a service-oriented architecture, helping to discover complex applications. Knowledge graph is a cross-cutting research hotspot in the fields of computer, knowledge engineering and information science.
Li Guodong +3 more
doaj +1 more source
Metalexicography as Knowledge Graph.
This short paper presents preliminary considerations regarding LexBib, a corpus, bibliography, and domain ontology of Lexicography and Dictionary Research, which is currently being developed at University of Hildesheim. The LexBib project is intended to provide a bibliographic metadata collection made available through an online reference platform. The
David Lindemann +2 more
openaire +4 more sources
A Survey on Knowledge Graph Structure and Knowledge Graph Embeddings
Knowledge Graphs (KGs) and their machine learning counterpart, Knowledge Graph Embedding Models (KGEMs), have seen ever-increasing use in a wide variety of academic and applied settings. In particular, KGEMs are typically applied to KGs to solve the link prediction task; i.e. to predict new facts in the domain of a KG based on existing, observed facts.
Jeffrey Sardina +2 more
openaire +2 more sources
Modelling stem cell differentiation related processes—A practical overview for biologists
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Structuring Knowledge in a Graph [PDF]
The idea that knowledge is a commodity that can be used by machines in various ways forms the entry to our discussion of knowledge based systems. We will limit ourselves to those systems that are in an active dialogue with their human user. As a consequence, the use and structuring of knowledge in autonomous systems, like robots or visual pattern ...
Stokman, Frans N., Vries, Pieter H. de
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