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LinkedImm: a linked data graph database for integrating immunological data [PDF]
BMC Bioinformatics, 2021 Background Many systems biology studies leverage the integration of multiple data types (across different data sources) to offer a more comprehensive view of the biological system being studied. While SQL (Structured Query Language) databases are popular
Syed Ahmad Chan Bukhari +4 more
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RELATIONAL DATABASE AND GRAPH DATABASE: A COMPARATIVE ANALYSIS [PDF]
Journal of Process Management and New Technologies, 2017 Since 1970, relational database models have been in use for storing, manipulating and retrieving data. The importance of relational databases is going to decrease due to the exponential growth of data as it is difficult to work with large number of ...
Surajit Medhi, Hemanta K. Baruah
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Functional querying in graph databases [PDF]
Vietnam Journal of Computer Science, 2017 The paper is focused on a functional querying in graph databases. We consider labelled property graph model and mention also the graph model behind XML databases. An attention is devoted to functional modelling of graph databases both at a conceptual and
Jaroslav Pokorný
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A cancer graph: a lung cancer property graph database in Neo4j [PDF]
BMC Research Notes, 2022 Objectives A novel graph data model of non-small cell lung cancer clinical and genomic data has been constructed with two aims: (1) provide a suitable model for facilitating graph analytics within the Neo4j framework or through tools which can interact ...
David Tuck
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Reactome graph database: Efficient access to complex pathway data. [PDF]
PLoS Computational Biology, 2018 Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data.
Antonio Fabregat +9 more
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Attack Graph to Graph Database
IOSR Journal of Computer Engineering, 2014 Databases are an integral part of almost any computing system today, and users heavily rely on the services they provide. When we interact with a computing system, we expect that any data be stored for future use, that the data is able to be looked up quickly, and that we can perform complex queries against the data stored in the database.
Iosr Journals, Saurav Saraff
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Graph Neural Networks on Graph Databases [PDF]
Training graph neural networks on large datasets has long been a challenge. Traditional approaches include efficiently representing the whole graph in-memory, designing parameter efficient and sampling-based models, and graph partitioning in a distributed setup. Separately, graph databases with native graph storage and query engines have been developed,
Dmytro Lopushanskyy, Borun Shi
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Real-Time Text-to-Cypher Query Generation with Large Language Models for Graph Databases [PDF]
Future InternetBased on their ability to efficiently and intuitively represent real-world relationships and structures, graph databases are gaining increasing popularity.
Markus Hornsteiner +5 more
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Conversion Method from Relational Database to Graph Database [PDF]
Jisuanji kexue, 2021 Due to the differences between the storage mode of relational database and graph database,during the process of transforming data in relational database to graph database,it is necessary to solve the main problems of edge definition,vertex uniqueness and
E Hai-hong, HAN Peng-hao, SONG Mei-na
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MULTI-RESOLUTION REPRESENTATION USING GRAPH DATABASE [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Multi-resolution representation has always been an important and popular data source for many research and applications, such as navigation, land cover, map generation, media event forecasting, etc.
Y. Huang, E. Stefanakis
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