Computing reliable gene expression levels from microarray experiments is a sophisticated process with many potential pitfalls. Quality control is one of the most important steps i...
Aim of this work is to apply a novel comprehensive machine learning tool for data mining to preprocessing and interpretation of gene expression data. Furthermore, some visualizatio...
Roberto Amato, Angelo Ciaramella, N. Deniskina, Ca...
Microarray data usually contains a high level of noisy gene data, the noisy gene data include incorrect, noise and irrelevant genes. Before Microarray data classification takes pla...
Background: With the rapid development of new genetic measurement methods, several types of genetic alterations can be quantified in a high-throughput manner. While the initial fo...
Background: Genome-wide expression studies have developed exponentially in recent years as a result of extensive use of microarray technology. However, expression signals are typi...