… the tools and methods that adopt integrative approach to analyze … This method uses a
Bayesian nonparametric model (… of integrative approach that helps in advancement of treatment …

… The test was performed using 60 eggs per treatment, divided into 3 … Dunn's test (for parametric
or non-parametric data, respectively) was … In this work, the microarray results indicate that …

… techniques have previously been used with microarray data. … is non-parametric, large in
size, and consists of mRNA-Z-score values. The Kruskal-Wallis test is a non-parametric method …

… -making process in the diagnosis and clinical management of … This technique has been
successfully applied to microarray … Kernel methods are powerful nonparametric modeling tools …

… from the integrative DNN. We also demonstrated … prognostic performance for survival
analysis. This highlights the benefit of integrating microarray and clinical data via our integrative …

… for the treatment of oncologic diseases. To facilitate cancer … non-parametric methods
Clin Cancer Res. 18:3677–85, 2012 … of Microarrays SAM samr (sam) The SAM is non-parametric …

… such as diseases prediction and diagnosis, cancer study and … a comprehensive survey
of studies on microarray cancer … actually survey the comprehensive approaches employed. …

… prognostic factor for CRC. Through a comprehensive analysis integrating tumor tissue arrays…
, and nonparametric methods, such as Kruskal–Wallis tests. To explore linear relationships, …

… by means of protein microarray and their serum level … protein microarray is an efficient
approach in discovering novel TAAbs which could be used as biomarkers in lung cancer diagnosis…

… may support rational, personalized planning of disease prevention or treatment. … microarray
gene expression profiling of lung or airway tissue from subjects with COPD obtained using …