Artificial intelligence re-analysis of gene array data identifies novel markers of urothelial cancer progression

Artificial intelligence re-analysis of gene array data identifies novel markers of urothelial cancer progression

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون:	Catto, J, Abbod, M, Linkens, D, Wild, P, Herr, A, Pilarsky, C, Wissman, C, Hartmann, A, Hamdy, F
التنسيق:	Conference item
منشور في:	2007

مواد مشابهة

Improving gene array analysis: The application of artificial intelligence identifies novel biomarkers of non invasive papillary bladder cancer progression
حسب: Wild, P, وآخرون
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Artificial intelligence and bladder cancer arrays.
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Artificial intelligence technique for gene expression profiling of urinary bladder cancer
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Artificial intelligence technique for gene expression profiling of urinary bladder cancer
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Application of artificial intelligence to the management of urological cancer
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Artificial intelligence for the prediction bladder cancer
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Less is more: artificial intelligence and gene-expression arrays.
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Predictive modeling in cancer: where systems biology meets the stock market.
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Development of a prognostic marker panel in bladder cancer using aberrant promoter methylation
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Promoter hypermethylation identifies progression risk in bladder cancer.
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Reply from Authors re: David J. DeGraff. Novel Use of a Combined Artificial Intelligence Approach to Identify Patients with Noninvasive Urothelial Cell Carcinoma of the Urinary Bladder Who Are at Greatest Risk for Progression to Muscle-Invasive Disease: A Step Forward. Eur Urol 2010; 57: 407-8
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Multifocal urothelial cancers with the mutator phenotype are of monoclonal origin and require panurothelial treatment for tumor clearance.
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Behavior of urothelial carcinoma with respect to anatomical location.
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DNA promoter methylation in urothelial cancer: a feature of the invasive phenotype and a novel therapeutic target
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Evidence for the early onset of aberrant promoter methylation in urothelial carcinoma.
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Immunohistochemical and molecular markers in urothelial carcinoma
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