Results 101 to 110 of about 7,092,434 (358)
Knowledge graph analysis of particles in Japanese [PDF]
The theory of knowledge graphs is a structuralistic theory of language. Its ontology consists of eight types of binary relationships and four types of so-called frames. The relationships connect so-called tokens, that represent semantic units.
Hoede, C.
core +1 more source
From omics to AI—mapping the pathogenic pathways in type 2 diabetes
Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan+2 more
wiley +1 more source
We propose a novel approach that uses semi-supervised learning to extract triplets from domain-specific texts and create a Knowledge Graph (KG), with a focus on the agricultural domain.
G. Veena, Deepa Gupta, Vani Kanjirangat
doaj +1 more source
Knowledge Graph Convolutional Networks for Recommender Systems [PDF]
To alleviate sparsity and cold start problem of collaborative filtering based recommender systems, researchers and engineers usually collect attributes of users and items, and design delicate algorithms to exploit these additional information. In general,
Hongwei Wang+4 more
semanticscholar +1 more source
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
A Knowledge Graph for Industry 4.0 [PDF]
One of the most crucial tasks for today’s knowledge workers is to get and retain a thorough overview on the latest state of the art. Especially in dynamic and evolving domains, the amount of relevant sources is constantly increasing, updating and overruling previous methods and approaches.
Sebastian R. Bader+4 more
openaire +1 more source
Tuberculosis remains a global health challenge and new therapeutic targets are required. Here, we characterized SseA, a sulfurtransferase from Mycobacterium tuberculosis involved in macrophage infection, and its interaction with the newly identified protein SufEMtb that activates SseA enzymatic activity.
Giulia Di Napoli+10 more
wiley +1 more source
Research on Digital Archives Service Mode Based on Knowledge Graph
[Purpose/significance] Aiming at shortcomings of the current service quality of digital archives, such as insufficient intelligence and single service content, this paper proposed to build an overall framework of ...
Xiong Huixiang, Yan Wuyue
doaj +1 more source
This work presents the characterization of MvoDUF2193, a Methanococcus voltae (Mvo) protein from the domain of unknown function (DUF) 2193 family. We demonstrate that MvoDUF2193 binds a single [4Fe–4S] cluster per subunit and that cluster occupancy regulates the transition from an apo tetramer to a [4Fe–4S] monomeric form. This structural transition is
Emily M. Dieter+8 more
wiley +1 more source
Cell‐free DNA aneuploidy score as a dynamic early response marker in prostate cancer
mFast‐SeqS‐based genome‐wide aneuploidy scores are concordant with aneuploidy scores obtained by whole genome sequencing from tumor tissue and can predict response to ARSI treatment at baseline and, at an early time point, to ARSI and taxanes. This assay can be easily performed at low cost and requires little input of cfDNA. Cell‐free circulating tumor
Khrystany T. Isebia+17 more
wiley +1 more source