Feature Selection and Classification of Microarray Gene Expression Data of Ovarian Carcinoma Patients using Weighted Voting Support Vector Machine

feature selection and classification of microarray gene expression data of ovarian carcinoma patients using weighted voting support vector machine

we can reach by dna microarray gene expression to such wealth of information with thousands of variables (genes). analysis of this information can show genetic reasons of disease and tumor differences. in this study we try to reduce high-dimensional data by statistical method to select valuable genes with high impact as biomarkers and then classify ovarian tumor based on gene expression data of...

Feature Selection in Tumor Classification Using Microarray Gene Expression Data

Feature selection is the process of choosing a subset of the original predictive variables through the elimination of redundant and uninformative representatives. An example of importance is the analysis of gene expression data from DNA microarray hybridization experiments. The data obtained from the experiments usually contain a few samples each with expression levels of a large number of gene...

Feature Selection for Cancer Classification Using Microarray Gene Expression Data

The DNA microarray technology enables us to measure the expression levels of thousands of genes simultaneously, providing great chance for cancer diagnosis and prognosis. The number of genes often exceeds tens of thousands, whereas the number of subjects available is often no more than a hundred. Therefore, it is necessary and important to perform gene selection for classification purpose. A go...

Modeling and design of a diagnostic and screening algorithm based on hybrid feature selection-enabled linear support vector machine classification

Background: In the current study, a hybrid feature selection approach involving filter and wrapper methods is applied to some bioscience databases with various records, attributes and classes; hence, this strategy enjoys the advantages of both methods such as fast execution, generality, and accuracy. The purpose is diagnosing of the disease status and estimating of the patient survival. Method...

Support Vector Machine Classi cation of Microarray Gene Expression Data

Support vector machine classification and validation of cancer tissue samples using microarray expression data

MOTIVATION DNA microarray experiments generating thousands of gene expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. We have developed a new method to analyse this kind of data using support vector machines (SVMs). This analysis consists of both classification of the tissue ...