Abstract
In recent years, in the post genomic era, more and more data is being generated by biological high throughput technologies, such as proteomics and transcriptomics. This omics data can be very useful, but the real challenge is to analyze all this data, as a whole, after integrating it. Biomedical data integration enables making queries to different, heterogeneous and distributed biomedical data sources. Data integration solutions can be very useful not only in the context of drug design, but also in biomedical information retrieval, clinical diagnosis, system biology, etc. In this review, we analyze the most common approaches to biomedical data integration, such as federated databases, data warehousing, multi-agent systems and semantic technology, as well as the solutions developed using these approaches in the past few years.
Keywords: Data integration, data warehouse, federated database, multi-agent systems, ontologies, semantic web technologies, Biomedical data, computational drug design, bioinformatics
Current Computer-Aided Drug Design
Title:Biomedical Data Integration in Computational Drug Design and Bioinformatics
Volume: 9 Issue: 1
Author(s): Jose A. Seoane, Vanessa Aguiar-Pulido, Cristian R. Munteanu, Daniel Rivero, Juan R. Rabunal, Julian Dorado and Alejandro Pazos
Affiliation:
Keywords: Data integration, data warehouse, federated database, multi-agent systems, ontologies, semantic web technologies, Biomedical data, computational drug design, bioinformatics
Abstract: In recent years, in the post genomic era, more and more data is being generated by biological high throughput technologies, such as proteomics and transcriptomics. This omics data can be very useful, but the real challenge is to analyze all this data, as a whole, after integrating it. Biomedical data integration enables making queries to different, heterogeneous and distributed biomedical data sources. Data integration solutions can be very useful not only in the context of drug design, but also in biomedical information retrieval, clinical diagnosis, system biology, etc. In this review, we analyze the most common approaches to biomedical data integration, such as federated databases, data warehousing, multi-agent systems and semantic technology, as well as the solutions developed using these approaches in the past few years.
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Cite this article as:
A. Seoane Jose, Aguiar-Pulido Vanessa, R. Munteanu Cristian, Rivero Daniel, R. Rabunal Juan, Dorado Julian and Pazos Alejandro, Biomedical Data Integration in Computational Drug Design and Bioinformatics, Current Computer-Aided Drug Design 2013; 9 (1) . https://dx.doi.org/10.2174/15734099112089990011
DOI https://dx.doi.org/10.2174/15734099112089990011 |
Print ISSN 1573-4099 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6697 |
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