Bioinformatics Integration Framework for Metabolic Pathway Data-Mining

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 pre-

DOI: 10.1007/11779568_98

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@inproceedings{Arredondo2006BioinformaticsIF, title={Bioinformatics Integration Framework for Metabolic Pathway Data-Mining}, author={Tom{\'a}s Arredondo and Michael Seeger and Lioubov Dombrovskaia and Jorge Avarias and Felipe Calder{\'o}n and Diego Candel and Freddy Mu{\~n}oz and Valeria Latorre-Reyes and Loreine Agull{\'o} and Macarena C{\'o}rdova and Luis G{\'o}mez}, booktitle={IEA/AIE}, year={2006} }