Computational framework to support integration of biomolecular and clinical data within a translational approach

• Published in: BMC bioinformatics 2013-06, Vol.14 (1), p.180-180, Article 180
• Main Authors: Miyoshi, Newton Shydeo Brandão, Pinheiro, Daniel Guariz, Silva, Jr, Wilson Araújo, Felipe, Joaquim Cezar
• Format: Article
• Language: English
• Subjects: Bioinformatics; Biological products; Biology; Biomedical Research; Carcinoma - genetics; Carcinoma - therapy; Computational biology; Computational Biology - methods; Databases, Factual; Genome, Human; Genomes; Genomics; Head and Neck Neoplasms - genetics; Head and Neck Neoplasms - therapy; Humans; Information management; Medical research; Medicine, Experimental; Ontology; Organisms; Semantics; Software; Translational Medical Research - methods
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/1471-2105-14-180

The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. We have implemented an extension of Chado - the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, exis