Abstract
In our study, we intend to investigate the mechanism of tolerance induction by the modulatory anti CD4 monoclonal antibody RIB 5/2 in insulin dependent diabetes mellitus rats. The aim of this investigation is to identify the key mechanisms of immune tolerance on the level of T cell, cytokine, and chemokine biomarkers in the blood, lymphatic organs, and pancreas. Additionally, it should be possible to define good biomarkers of autoimmunity and tolerance for prediction of diabetes onset. We mainly applied decision trees and later on some other classification algorithms on a rather small data set. Unfortunately, the results are not significant but are good enough to satisfy our biological partners.
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References
Akerblom, H.K., Vaarala, O., Hyoty, H., Ilonen, J., Knip, M.: Environmental factors in the etiology of type 1 diabetes. Am. J. Med. Genet. 115, 18–29 (2002)
Jun, H.S., Yoon, J.W.: A new look at viruses in type 1 diabetes. Diabetes Metab. Res. Rev. 19, 8–31 (2003)
Ludvigsson, J., Faresjo, M., Hjorth, M., et al.: GAD treatment and insulin secretion in recent-onset type 1 diabetes. N. Engl. J. Med. 359, 1909–1920 (2008)
D’Hertog, W., Overbergh, L., Lage, K., et al.: Proteomics analysis of cytokine-induced dysfunction and death in insulin-producing INS-1E cells: new insights into the pathways involved. Mol. Cell Proteomics 6(21), 80–99 (2007)
Rasschaert, J., Liu, D., Kutlu, B., Cardozo, A.K., Kruhoffer, M., ØRntoft, T.F., Eizirik, D.L.: Global profiling of double stranded RNA- and IFN-gamma-induced genes in rat pancreatic beta cells. Diabetologia 46, 1641–1657 (2003)
Gysemans, C., Callewaert, H., Overbergh, L., Mathieu, C.: Cytokine signalling in the beta-cell: a dual role for IFNgamma. Biochem. Soc. Trans. 36, 328–333 (2008)
Lampeter, E.F., McCann, S.R., Kolb, H.: Transfer of diabetes type 1 by bone-marrow transplantation. Lancet 351, 568–569 (1998)
Schloot, N.C., Roep, B.O., Wegmann, D.R., Yu, L., Wang, T.B., Eisenbarth, G.S.: T-cell reactivity to GAD65 peptide sequences shared with coxsackie virus protein in recent-onset IDDM, post-onset IDDM patients and control subjects. Diabetologia 40, 332–338 (1997)
Quinlan, J.R.: C4.5 Programs for Machine Learning. Morgan Kaufmann, San Mateo (1993)
Hall, M., et al.: The WEKA data mining software: An update. SIGKDD Explorations 11(1), 10–18 (2009)
Gan, Z., Chow, T.W., Huang, D.: Effective Gene Selection Method Using Bayesian Discriminant Based Criterion and Genetic Algorithms. Journal of Signal Processing Systems 50, 293–304 (2008)
Cost, S., Salzberg, S.: A weighted Nearest Neighbor Algorithm for Learning with Symbolic Features. Machine Learning 10(1), 57–78 (1993)
Breiman, L.: Random Forest. Machine Learning 45(1), 5–32 (2001)
Platt, J.: Avances in Large Margin Classifiers, pp. 61–74. MIT-Press (1999)
Bichindaritz, I.: Methods in Case-Based Classification in Bioinformatics: Lessons Learned. In: Perner, P. (ed.) ICDM 2011. LNCS, vol. 6870, pp. 300–313. Springer, Heidelberg (2011)
Perner, J., Zotenko, E.: Characterizing Cell Types through Differentially Expressed Gene Clusters Using a Model-Based Approach. In: Perner, P. (ed.) ICDM 2011. LNCS, vol. 6870, pp. 106–120. Springer, Heidelberg (2011)
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Schmidt, R., Weiss, H., Fuellen, G. (2012). Application of Classification Algorithms on IDDM Rat Data. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2012. Lecture Notes in Computer Science(), vol 7377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31488-9_1
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