Semantic unification and search of bioinformatics databases
Конференцијски прилог (Објављена верзија)
,
© 2023 Institute of Molecular Genetics and Genetic Engineering, University of Belgrade
Метаподаци
Приказ свих података о документуАпстракт
Analyzing biological data from various sources offers a comprehensive perspective of a
domain, facilitating the identification of patterns that would otherwise be challenging or
impossible to observe when focusing solely on individual biological entities. The process
of linking data from different databases can present challenges due to inconsistencies in
properties and identifiers assigned to the same entity across databases. Although certain
databases include a range of identifiers from multiple sources, the search capabilities
are restricted to exact property matching, preventing the execution of complex queries
involving multiple metadata attributes.
We designed a novel data framework that aims to address these challenges by facilitating
the linkage and retrieval of information from diverse interconnected biological data
sources. To evaluate the effectiveness of the model, we conducted tests and created a
knowledge graph using metadata extracted from five separate public... datasets: DisProt,
HGNC, Tantigen 2.0, IEDB, and DisGeNET. The resulting graph establishes connections
between more than 17 million nodes, comprising 2.5 million distinct biological entity
objects, and encompasses over 4 million relationships.
Additionally, we designed and implemented a general-purpose procedure for extracting
new relationships based on semantic similarity from data transformed into the BioGraph
data model.
Кључне речи:
biioinformatics database / semantic search / unification / BioGraphИзвор:
4th Belgrade Bioinformatics Conference, 2023, 4, 63-63Издавач:
- Belgrade : Institute of molecular genetics and genetic engineering
Напомена:
- Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 2023
Колекције
Институција/група
Institut za molekularnu genetiku i genetičko inženjerstvoTY - CONF AU - Veljković, Aleksandar AU - Mitić, N. PY - 2023 UR - https://belbi.bg.ac.rs/ UR - https://imagine.imgge.bg.ac.rs/handle/123456789/2003 AB - Analyzing biological data from various sources offers a comprehensive perspective of a domain, facilitating the identification of patterns that would otherwise be challenging or impossible to observe when focusing solely on individual biological entities. The process of linking data from different databases can present challenges due to inconsistencies in properties and identifiers assigned to the same entity across databases. Although certain databases include a range of identifiers from multiple sources, the search capabilities are restricted to exact property matching, preventing the execution of complex queries involving multiple metadata attributes. We designed a novel data framework that aims to address these challenges by facilitating the linkage and retrieval of information from diverse interconnected biological data sources. To evaluate the effectiveness of the model, we conducted tests and created a knowledge graph using metadata extracted from five separate public datasets: DisProt, HGNC, Tantigen 2.0, IEDB, and DisGeNET. The resulting graph establishes connections between more than 17 million nodes, comprising 2.5 million distinct biological entity objects, and encompasses over 4 million relationships. Additionally, we designed and implemented a general-purpose procedure for extracting new relationships based on semantic similarity from data transformed into the BioGraph data model. PB - Belgrade : Institute of molecular genetics and genetic engineering C3 - 4th Belgrade Bioinformatics Conference T1 - Semantic unification and search of bioinformatics databases EP - 63 SP - 63 VL - 4 UR - https://hdl.handle.net/21.15107/rcub_imagine_2003 ER -
@conference{ author = "Veljković, Aleksandar and Mitić, N.", year = "2023", abstract = "Analyzing biological data from various sources offers a comprehensive perspective of a domain, facilitating the identification of patterns that would otherwise be challenging or impossible to observe when focusing solely on individual biological entities. The process of linking data from different databases can present challenges due to inconsistencies in properties and identifiers assigned to the same entity across databases. Although certain databases include a range of identifiers from multiple sources, the search capabilities are restricted to exact property matching, preventing the execution of complex queries involving multiple metadata attributes. We designed a novel data framework that aims to address these challenges by facilitating the linkage and retrieval of information from diverse interconnected biological data sources. To evaluate the effectiveness of the model, we conducted tests and created a knowledge graph using metadata extracted from five separate public datasets: DisProt, HGNC, Tantigen 2.0, IEDB, and DisGeNET. The resulting graph establishes connections between more than 17 million nodes, comprising 2.5 million distinct biological entity objects, and encompasses over 4 million relationships. Additionally, we designed and implemented a general-purpose procedure for extracting new relationships based on semantic similarity from data transformed into the BioGraph data model.", publisher = "Belgrade : Institute of molecular genetics and genetic engineering", journal = "4th Belgrade Bioinformatics Conference", title = "Semantic unification and search of bioinformatics databases", pages = "63-63", volume = "4", url = "https://hdl.handle.net/21.15107/rcub_imagine_2003" }
Veljković, A.,& Mitić, N.. (2023). Semantic unification and search of bioinformatics databases. in 4th Belgrade Bioinformatics Conference Belgrade : Institute of molecular genetics and genetic engineering., 4, 63-63. https://hdl.handle.net/21.15107/rcub_imagine_2003
Veljković A, Mitić N. Semantic unification and search of bioinformatics databases. in 4th Belgrade Bioinformatics Conference. 2023;4:63-63. https://hdl.handle.net/21.15107/rcub_imagine_2003 .
Veljković, Aleksandar, Mitić, N., "Semantic unification and search of bioinformatics databases" in 4th Belgrade Bioinformatics Conference, 4 (2023):63-63, https://hdl.handle.net/21.15107/rcub_imagine_2003 .