CNS Tumor Prediction Using Gene Expression Data Part II
نویسندگان
چکیده
In this chapter, we propose a novel algorithm for characterizing a variety of CNS tumors. The proposed algorithm is illustrated with an analysis of an Affymetrix gene expression data from CNS tumor samples (Pomeroy et al., 2002). As discussed in the previous chapter entitled: CNS Tumor Prediction Using Gene Expression Data Part I, we used an ANOVA model to normalize the microarray gene expression measurements. In this chapter, we introduce a systemic way of building tumor prototypes to facilitate automatic prediction of CNS tumors.
منابع مشابه
CNS Tumor Prediction Using Gene Expression Data Part I
Automated diagnosis and prognosis of tumors of the central nervous system (CNS) offer overwhelming challenges because of heterogeneous phenotype and genotype behavior of tumor cells (Yang et al. 2003, Pomeroy et al. 2002). Unambiguous characterization of these tumors is essential for accurate prognosis and therapy. Although the present imaging techniques help to explore the anatomical features ...
متن کاملFeature 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...
متن کاملPrediction of blood cancer using leukemia gene expression data and sparsity-based gene selection methods
Background: DNA microarray is a useful technology that simultaneously assesses the expression of thousands of genes. It can be utilized for the detection of cancer types and cancer biomarkers. This study aimed to predict blood cancer using leukemia gene expression data and a robust ℓ2,p-norm sparsity-based gene selection method. Materials and Methods: In this descriptive study, the microarray ...
متن کاملADAM Gene Expression in The Adult CNS and Genetic Aberrations in Cancer Cells
ADAM metalloprotease-disintegrins share a common modular structure of functional domains for proteolytic, cell adhesion, and signaling interactions. The metalloprotease domain of oughly half of the known ADAMs contain an intact consensus metzincin catalytic site, and they are thus thought to function as active metalloproteases. The types of interactions mediated by ADAMs are expressly conspicu...
متن کاملبررسی بیان ژن مهارکننده توموری TUSC1 (Tumor suppressor candidate gene 1) در نمونههای بافتی سرطان پستان و همراهی آن با میزان تومورزایی
Introduction: Breast cancer remains the prominent cause of mortality in women. Several biomarkers are used to evaluation the response and targeting to therapy. Tumor suppressor candidate 1 (TUSC1) gene was newly identified as a probable tumor suppressor in human cancers. Nevertheless, the expression and potential function of TUSC1 in breast cancer stay undecided. Therefore, this study aimed the...
متن کامل