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Identification of transmembrane segments in protein sequences is an important issue in the field of bioinformatics. In this study, a method is proposed for linear discrimination between transmembrane and non-transmembrane segments, combining chemical and statistical features of the proteins with higher-order crossings analysis for protein segment classification. The method was tested on human proteins...
Heuristical algorithms can reduce the computational complexity. Such methods require of some stopping criteria (cost function). Some of these cost functions are based on statistics like univariate and multivariate methods of analysis. Dimensional reduction techniques such as principal component analysis (PCA) allow to find a lower dimension transformed space based on data variance, but this procedure...
A latent-threshold model and misclassification algorithm were implemented to examine potential misdiagnosis among 16 Alzheimer's disease (AD) subjects using gene expression data. Results obtained without invoking the misclassification algorithm showed limited predictive power of the model. When the misclassification algorithm was invoked, four subjects were identified as being potentially misdiagnosed...
Identification of transmembrane segments in protein sequences is an important issue in the field of bioinformatics. In this study, a method is proposed for linear discrimination between transmembrane and non-transmembrane segments, combining chemical and statistical features of the proteins with higher-order crossings analysis for protein segment classification. The method was tested on human proteins...
Heuristical algorithms can reduce the computational complexity. Such methods require of some stopping criteria (cost function). Some of these cost functions are based on statistics like univariate and multivariate methods of analysis. Dimensional reduction techniques such as principal component analysis (PCA) allow to find a lower dimension transformed space based on data variance, but this procedure...
A latent-threshold model and misclassification algorithm were implemented to examine potential misdiagnosis among 16 Alzheimer's disease (AD) subjects using gene expression data. Results obtained without invoking the misclassification algorithm showed limited predictive power of the model. When the misclassification algorithm was invoked, four subjects were identified as being potentially misdiagnosed...
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