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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Arredondo, T. V., Seeger, M. P., Dombrovskaia, L., Avarias, J. A., Calderón, F. B., Candel, D. C., … Gómez, L. (2006). Bioinformatics integration framework for metabolic pathway data-mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4031 LNAI, pp. 917–926). Springer Verlag. https://doi.org/10.1007/11779568_98
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