Bioinformatics Integration Framework for Metabolic Pathway Data-Mining

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 i...

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Bibliographic Details
Published inAdvances in Applied Artificial Intelligence pp. 917 - 926
Main Authors Tomás, Arredondo V., Michael, Seeger P., Dombrovskaia, Lioubov, Jorge, Avarias A., Felipe, Calderón B., Diego, Candel C., Freddy, Muñoz R., Valeria, Latorre R., Agulló, Loreine, Macarena, Cordova H., Gómez, Luis
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2006
SeriesLecture Notes in Computer Science
Subjects
Acidithiobacillus Ferrooxidans
Fuzzy Logic
Metabolic Network
Metabolic Path
Metabolic Pathway
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Summary: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.
ISBN:3540354530
9783540354536
ISSN:0302-9743
1611-3349
DOI:10.1007/11779568_98