Results 161 to 170 of about 7,645,086 (295)

Advancing drug-target interaction prediction: a comprehensive graph-based approach integrating knowledge graph embedding and ProtBert pretraining. [PDF]

BMC Bioinformatics, 2023
Djeddi WE, Hermi K, Ben Yahia S, Diallo G.   +3 more
europepmc   +1 more source

Mitigating Cancer Therapy–Related Cognitive Impairment by Targeted Activation of Undruggable Phosphatase

Advanced Science, EarlyView.
An RVG‑engineered exosomal saRNA delivery system (RVG‑EVs‑saPtpro) effectively targets and activates hippocampal PTPRO, functioning as a “molecular brake” to alleviate cancer therapy‑related cognitive impairment (CTRCI) by enhancing neuronal survival, neurogenesis, and synaptic plasticity.
Zhimeng Yao, Yuhua Meng, Huanyi Li, Yinhui Jiang, Xiaona Lin, Mengyuan Hu, Qing Liu, Xiaofu Qiu, Hongzheng Ren, Yunlong Pan, Bin Pan, Zexiong Guo, Shuyao Zhang, Dianzheng Zhang, Li Yang, Shegan Gao, Weijing Deng, Jianfan Chen, Hao Zhang   +18 more
wiley   +1 more source

Knowledge graph embedding for profiling the interaction between transcription factors and their target genes. [PDF]

PLoS Comput Biol, 2023
Wu YH, Huang YA, Li JQ, You ZH, Hu PW, Hu L, Leung VCM, Du ZH.   +7 more
europepmc   +1 more source

MASH Background Confers Enhanced Disease Susceptibility and Acetaminophen Toxicity in iPSC‐Derived Liver Organoids

Advanced Science, EarlyView.
This work establishes a novel method for generating multicellular liver organoids from control and MASH donor iPSCs. The model recapitulates several disease‐specific characteristics, with MASH donor‐derived organoids showing higher susceptibility. Lipidomic profiling of MASH organoids closely resembles MASH liver biopsies.
Ekta Minocha, Ashwani Kumar Gupta, Nate Schmidt, Richard M. Green, John G. Purdy, Jason A. Wertheim   +5 more
wiley   +1 more source

Static detection method for multi-level network source code vulnerabilities based on knowledge graph technology

Discover Artificial Intelligence
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, Lina Zhang, Ying Yan, Zhenhong Zhang   +3 more
doaj   +1 more source

Predicting protein and pathway associations for understudied dark kinases using pattern-constrained knowledge graph embedding. [PDF]

PeerJ, 2023
Salcedo MV, Gravel N, Keshavarzi A, Huang LC, Kochut KJ, Kannan N.   +5 more
europepmc   +1 more source

Fact Validation with Knowledge Graph Embeddings.

, 2019
Fact validation in a knowledge graph is a task to determine whether a given fact (subject, predicate, object) should appear in the knowledge graph. In this paper, we have described our approach for the fact validation task in the context of the Semantic Web Challenge 2019.
Ammar, Ammar, Çelebi, Remzi
openaire   +2 more sources

Knowledge graph embedding models for automatic commonsense knowledge acquisition

, 2019
Intelligent systems are expected to make smart human-like decisions based on accumulated commonsense knowledge of an average individual. These systems need, therefore, to acquire an understanding about uses of objects, their properties, parts and ...
Ikhlas Mohammad Suliman Alhussien
core   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Combining the External Medical Knowledge Graph Embedding to Improve the Performance of Syndrome Differentiation Model. [PDF]

Evid Based Complement Alternat Med, 2023
Ye Q, Yang R, Cheng CL, Peng L, Lan Y.
europepmc   +1 more source