Bioinformatics integration framework for metabolic pathway data-mining

Authors:
Arredondo V. Tomás;Seeger P. Michael;Lioubov Dombrovskaia;Avarias A. Jorge;Calderón B. Felipe;Candel C. Diego;Muñoz R. Freddy;Latorre R. Valeria;Loreine Agulló;Cordova H. Macarena;Luis Gómez
Affiliations:
Departamento de Electrónica;Millennium Nucleus EMBA, Departamento de Química;Departamento de Informática, Universidad Técnica Federico Santa María, Valparaíso, Chile;Departamento de Informática, Universidad Técnica Federico Santa María, Valparaíso, Chile;Departamento de Informática, Universidad Técnica Federico Santa María, Valparaíso, Chile;Departamento de Informática, Universidad Técnica Federico Santa María, Valparaíso, Chile;Departamento de Informática, Universidad Técnica Federico Santa María, Valparaíso, Chile;Millennium Nucleus EMBA, Departamento de Química;Millennium Nucleus EMBA, Departamento de Química;Millennium Nucleus EMBA, Departamento de Química;Millennium Nucleus EMBA, Departamento de Química
Venue:
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Year:
2006

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Abstract

A vast amount of bioinformatics information is continuously being introduced to different databases around the world. Handling the various applications used to study this information present a major data management and analysis challenge to researchers. The present work investigates the problem of integrating heterogeneous applications and databases towards providing a more efficient data-mining environment for bioinformatics research. A framework is proposed and GeXpert, an application using the framework towards metabolic pathway determination is introduced. Some sample implementation results are also presented.