Titlebook: Intelligent Data Engineering and Automated Learning - IDEAL 2004; 5th International Co Zheng Rong Yang,Hujun Yin,Richard M. Everson Confere

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Unsupervised Dense Regions Discovery in DNA Microarray Dataregions are of statistical and biological significance through experiments. A dataset containing gene expression levels of 23 primate brain samples is employed to test our algorithms. Subsets of potential genes distinguishing between species and a subset of samples with potential abnormalities are i

Rodent

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Exploring Dependencies Between Yeast Stress Genes and Their Regulatorssuch common properties by models that maximize common variation, and explore potential regulators of the stress response by further maximizing mutual information with transcription factor binding data. A computationally tractable combination of generalized canonical correlations and clustering that

Traumatic-Grief

Poly-transformationansformation multiple transformations of the data are made before learning (data mining) is applied. The theoretical basis for poly-transformation is the same as that for other combining methods – using different predictors to remove uncorrelated errors. It is not possible to demonstrate the utility

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Prediction of Natively Disordered Regions in Proteins Using a Bio-basis Function Neural Networkudy and detection of such disordered regions is very important both for facilitating structural analysis and to aid understanding of protein function. A newly developed pattern recognition algorithm termed a “Bio-basis Function Neural Network” has been applied to the detection of disordered regions

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PromSearch: A Hybrid Approach to Human Core-Promoter Predictioncombines search-by-content method and search-by-signal method. Global statistics of promoter-specific contents are included to represent new significant information underlying the proximal and downstream region around transcription start site (TSS) of DNA sequence. Local signal features such as TATA

heterogeneous

Synergy of Logistic Regression and Support Vector Machine in Multiple-Class Classificatione out a hybrid multi-class classifier with very promising results in terms of classification accuracy. Usually, the multiple-class classifier can be built by using many binary classifiers as its construction bases. Those binary classifiers might be trained by either one-versus-one or one-versus-othe

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Zhiyuan Luo,Tony Bellotti,Alex Gammermanht gewidmet werden muß. Es wurde u. a. auf die aberrierenden Gallengänge hingewiesen, welche vom Leberbett aus direkt in die Gallenblase einmünden können und deren Außerachtlassung bei der Cholecystektomie zu postoperativem Gallenfluß, oft von beträchtlicher Stärke, führen kann. Wenn bei einer Chole