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Rapid development of entity-based data models for bioinformatics with persistence object-oriented design and structured interfaces

Overview of attention for article published in BioData Mining, March 2017
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Title
Rapid development of entity-based data models for bioinformatics with persistence object-oriented design and structured interfaces
Published in
BioData Mining, March 2017
DOI 10.1186/s13040-017-0130-z
Pubmed ID
Authors

Elishai Ezra Tsur

Abstract

Databases are imperative for research in bioinformatics and computational biology. Current challenges in database design include data heterogeneity and context-dependent interconnections between data entities. These challenges drove the development of unified data interfaces and specialized databases. The curation of specialized databases is an ever-growing challenge due to the introduction of new data sources and the emergence of new relational connections between established datasets. Here, an open-source framework for the curation of specialized databases is proposed. The framework supports user-designed models of data encapsulation, objects persistency and structured interfaces to local and external data sources such as MalaCards, Biomodels and the National Centre for Biotechnology Information (NCBI) databases. The proposed framework was implemented using Java as the development environment, EclipseLink as the data persistency agent and Apache Derby as the database manager. Syntactic analysis was based on J3D, jsoup, Apache Commons and w3c.dom open libraries. Finally, a construction of a specialized database for aneurysms associated vascular diseases is demonstrated. This database contains 3-dimensional geometries of aneurysms, patient's clinical information, articles, biological models, related diseases and our recently published model of aneurysms' risk of rapture. Framework is available in: http://nbel-lab.com.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 31%
Researcher 4 31%
Professor 1 8%
Librarian 1 8%
Unknown 3 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 31%
Computer Science 2 15%
Medicine and Dentistry 2 15%
Social Sciences 1 8%
Agricultural and Biological Sciences 1 8%
Other 0 0%
Unknown 3 23%