BioSNI: A Semantic Network Integration Approach for Biological Data
T. A. Soliman
Abstract
T. A. Soliman
Abstract
Recently, the world is hunting for using life sciences data in solving the problems of fighting hunger in the next coming years. Integrating this data can be useful in areas of agricultural bioinformatics and other disciplines. However, efficient integration techniques must be developed to biological data since biological data has its own challenging characteristics, such as the existence of huge data existence, heterogeneous distributed data, and frequently updated data. In the current work, a semantic network for biological data integration is proposed, utilizing both ontology provided at OBO and atomic data provided at various biological databases to encompass an integrated data layer that can be queried using XQuery. Human and Yeast proteins are used as examples from UniProt release 14, integrated with other protein-related data, such as protein-protein interaction, protein domain, protein function, protein subcellular location, and related chemical reactions.
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Recently, the world is hunting for using life sciences data in solving the problems of fighting hunger in the next coming years. Integrating this data can be useful in areas of agricultural bioinformatics and other disciplines. However, efficient integration techniques must be developed to biological data since biological data has its own challenging characteristics, such as the existence of huge data existence, heterogeneous distributed data, and frequently updated data. In the current work, a semantic network for biological data integration is proposed, utilizing both ontology provided at OBO and atomic data provided at various biological databases to encompass an integrated data layer that can be queried using XQuery. Human and Yeast proteins are used as examples from UniProt release 14, integrated with other protein-related data, such as protein-protein interaction, protein domain, protein function, protein subcellular location, and related chemical reactions.
Key concepts: Biological data, Computer science, Data integration, UniProt, Biological database, Biological network, Ontology, Data science