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.
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References
Arredondo, T., Neelakanta, P.S., DeGroff, D.: Fuzzy Attributes of a DNA Complex: Development of a Fuzzy Inference Engine for Codon-’Junk’ Codon Delineation. Artif. Intell. Med. 35(1-2), 87–105 (2005)
Barker, J., Thornton, J.: Software Engineering Challenges in bioinformatics. In: Proceedings of the 26th International Conference on Software Engineering. IEEE, Los Alamitos (2004)
Bernardi, M., Lapi, M., Leo, P., Loglisci, C.: Mining Generalized Association Rules on Biomedical Literature. In: Moonis, A., Esposito, F. (eds.) Innovations in Applied Artificial Intelligence. LNCS (LNAI), vol. 3353, pp. 500–509. Springer, Heidelberg (2005)
Brown, T.A.: Genomes. John Wiley and Sons, NY (1999)
Cary, M.P., Bader, G.D., Sander, C.: Pathway information for systems biology (Review Article). FEBS Lett. 579, 1815–1820 (2005)
Claverlie, J.M.: Bioinformatics for Dummies. Wiley, Chichester (2003)
Cámara, B., Herrera, C., González, M., Couve, E., Hofer, B., Seeger, M.: From PCBs to highly toxic metabolites by the biphenyl pathway. Environ. Microbiol. (6), 842–850 (2004)
Cohen, J.: Computer Science and Bioinformatics. Commun. ACM 48(3), 72–79 (2005)
Costa, M., Collins, R., Anterola, A., Cochrane, F., Davin, L., Lewis, N.: An in silico assessment of gene function and organization of the phenylpropanoid pathway metabolic networks in Arabidopsis thaliana and limitations thereof. Phytochem. 64, 1097–1112 (2003)
CO-Drive project: http://hci.cs.concordia.ca/www/hcse/projects/CO-DRIVE/
Durbin, R.: Biological Sequence Analysis, Cambridge, UK (2001)
Eclipse project: http://www.eclipse.org
Entrez NCBI Database: www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Nucleotide
Gardner, D.: Using genomics to help predict drug interactions. J. Biomed. Inform. 37, 139–146 (2004)
GeXpert sourceforge page: http://sourceforge.net/projects/gexpert
Javahery, H., Seffah, A., Radhakrishnan, T.: Beyond Power: Making Bioinformatics Tools User-Centered. Commun. ACM 47, 11 (2004)
Jimenez, J.I., Miñambres, B., García, J., Díaz, E.: Genomic insights in the metabolism of aromatics compounds in Pseudomonas. In: Ramos, J.L. (ed.) Pseudomonas, vol. 3, pp. 425–462. Kluwer Academic Publishers, NY (2004)
Larman, C.: Applying UML and Patterns: An Introduction to Object-Oriented Analysis and Design and Iterative Development. Prentice Hall PTR, Englewood Cliffs (2004)
Loew, L.W., Schaff, J.C.: The Virtual Cell: a software environment for computational cell biology. Trends Biotechnol. 19, 10 (2001)
Ma, H., Zeng, A.: Reconstruction of metabolic networks from genome data and analysis of their global structure for various organisms. Bioinformatics 19, 270–277 (2003)
Magalhaes, J., Toussaint, O.: How bioinformatics can help reverse engineer human aging. Aging Res. Rev. 3, 125–141 (2004)
Molidor, R., Sturn, A., Maurer, M., Trajanosk, Z.: New trends in bioinformatics: from genome sequence to personalized medicine. Exp. Gerontol. 38, 1031–1036 (2003)
Neelakanta, P.S., Arredondo, T., Pandya, S., DeGroff, D.: Heuristics of AI-Based Search Engines for Massive Bioinformatic Data-Mining: An Example of Codon/Noncodon Delineation Search in a Binary DNA Sequence. In: Proceeding of IICAI (2003)
Papin, J.A., Price, N.D., Wiback, S.J., Fell, D.A., Palsson, B.O.: Metabolic Pathways in the Post-genome Era. Trends Biochem. Sci. 18, 5 (2003)
Pocock, M., Down, T., Hubbard, T.: BioJava: Open Source Components for Bioinformatics. ACM SIGBIO Newsletter 20(2), 10–12 (2000)
Rojdestvenski, I.: VRML metabolic network visualizer. Comp. Bio. Med. 33 (2003)
SBML: Systems Biology Markup Language, http://sbml.org/index.psp
Segal, T., Barnard, R.: Let the shoemaker make the shoes - An abstraction layer is needed between bioinformatics analysis, tools, data, and equipment: An agenda for the next 5 years. In: First Asia-Pacific Bioinformatics Conference, Australia (2003)
Seeger, M., Timmis, K.N., Hofer, B.: Bacterial pathways for degradation of polychlorinated biphenyls. Mar. Chem. 58, 327–333 (1997)
Sun, J., Zeng, A.: IdentiCS - Identification of coding sequence and in silico reconstruction of the metabolic network directly from unannotated low-coverage bacterial genome sequence. BMC Bioinformatics 5(112) (2004)
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Tomás, A.V. et al. (2006). Bioinformatics Integration Framework for Metabolic Pathway Data-Mining. In: Ali, M., Dapoigny, R. (eds) Advances in Applied Artificial Intelligence. IEA/AIE 2006. Lecture Notes in Computer Science(), vol 4031. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11779568_98
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DOI: https://doi.org/10.1007/11779568_98
Publisher Name: Springer, Berlin, Heidelberg
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