Learning Curves in Classification With Microarray Data

Clustering Microarray Data with Space Filling Curves

We introduce a new clustering method for DNA microarray data that is based on space filling curves and wavelet denoising. The proposed method is much faster than the established fuzzy c-means clustering because clustering occurs in one dimension and it clusters cells that contain data, instead of data themselves. Moreover, preliminary evaluation results on data sets from Small Round Blue-Cell t...

cDNA Microarray Data Normalization

microarray data analysis for detection and classification of viral infection

dna microarrays consist of collection of dna microscopic spots that in order to form an array attached to a solid surface such as glass, plastic or silicon chip. the pieces of fixed dna considered as a searcher. in this technology it is possible to test sample against thousands probes for specific genes. with this ability, arrays accelerate the biological investigations, gene finding, molecular...

Cancer classification using Machine Learning Technique on Microarray Data

The challenge of cancer treatment has been to identify distinct tumor types to enable the selection of specific therapies aimed to maximize efficacy and minimize toxicity. Improvements in cancer classifications have thus been central in the advances of cancer treatment. Today, most cancer classifications have been based primarily on morphological appearance of the tumor cell determined by the o...

New Ensemble Learning Approaches for Microarray Data Classification

A reliable and precise classification of tumors is essential for successful treatment of cancer. Microarray technologies allow the rapid and comprehensive assessment of the transcriptional activity of a cell, leading to a more comprehensive understanding of the molecular variations among tumors and, hence, to a finer informative classification. However, the major challenge in using this technol...