Results 121 to 130 of about 2,770 (172)

Petagraph: A large-scale unifying knowledge graph framework for integrating biomolecular and biomedical data. [PDF]

Sci Data
Stear BJ, Mohseni Ahooyi T, Simmons JA, Kollar C, Hartman L, Beigel K, Lahiri A, Vasisht S, Callahan TJ, Nemarich CM, Silverstein JC, Taylor DM.   +11 more
europepmc   +1 more source

The immunoproteome and multimorbidity: A Mendelian randomization study. [PDF]

Sci Adv
Hukerikar N, Hingorani AD, Chopade S, Cupido AJ, Asselbergs FW, Finan C, Schmidt AF.   +6 more
europepmc   +1 more source

A dataset on vulnerabilities affecting dependencies in software package managers. [PDF]

Data Brief
Márquez AG, Varela-Vaca ÁJ, Gómez López MT.   +2 more
europepmc   +1 more source

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery. [PDF]

Mach Learn Sci Technol
Zimmermann Y, Bazgir A, Al-Feghali A, Ansari M, Bocarsly J, Brinson LC, Chiang Y, Circi D, Chiu MH, Daelman N, Evans ML, Gangan AS, George J, Harb H, Khalighinejad G, Takrim Khan S, Klawohn S, Lederbauer M, Mahjoubi S, Mohr B, Mohamad Moosavi S, Naik A, Beste Ozhan A, Plessers D, Roy A, Schöppach F, Schwaller P, Terboven C, Ueltzen K, Wu Y, Zhu S, Janssen J, Li C, Foster I, Blaiszik B.   +34 more
europepmc   +1 more source

MTB-ImmunogenKG: An LLM-assisted knowledge graph for antigen selection in tuberculosis vaccine research. [PDF]

Biosaf Health
Peng J, Zhuang X, Chen Y, Xu H, Du Y, Zhu B, Zhao G, Wang Y, Ling Y, Zhang G.   +9 more
europepmc   +1 more source

Building an intelligent diabetes Q&A system with knowledge graphs and large language models. [PDF]

Front Public Health
Qin Z, Wu D, Zang Z, Chen X, Zhang H, Wong CUI.   +5 more
europepmc   +1 more source

Cross-Species Aging Knowledge Integration into Agentic AI Platform Uncovers Conserved Mechanisms

Ahuja G, Sharma A, Singh A, Kedia S, Sharma A, Gautam V, Sharma P, Khandelwal A, Ramakrishna S, Muddashetty R, Freude K, Solanki S, Chauhan S, Kumar S, Satija S, Duari S, Arora S, Gupta A, Shome R, Sengupta D, nair D.   +20 more
europepmc   +1 more source

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Supporting Data Types in Neo4j

Communications in Computer and Information Science, 2022
The use of graph databases has grown over the years, creating the need to use many of the features available in relational databases. Several of these features are already in use, but since graph databases are still in a develop-ment phase, many concepts supported in relational databases are still not supported in graph databases.
Kornelije Rabuzin
exaly   +2 more sources

Analysis of film data based on Neo4j

2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS), 2017
Film data analysis is important for website to find relationship between film data. Other than normal relational database, a novel and popular graph database, Neo4j uses graph related concepts to describe data models, the data can easily be nodes, edges and their associated attributes. By focusing on film data, Neo4j-based analysis is conducted in this
Zhiguo Hong, Minyong Shi
exaly   +2 more sources

Neo4j Keys

, 2020
Keys play a fundamental role in every data model. They stipulate how real-world entities are identified in the database but also how to physically and logically organize access to data. Neo4j is currently the most popular graph database management system.
Link, Sebastian
openaire   +2 more sources