Characteristic attributes in cancer microarrays

Rapid advances in genome sequencing and gene expression microarray technologies are providing unprecedented opportunities to identify specific genes involved in complex biological processes, such as development, signal transduction, and disease. The vast amount of data generated by these technologies has presented new challenges in bioinformatics. To help organize and interpret microarray data, new and efficient computational methods are needed to: (1) distinguish accurately between different biological or clinical categories (e.g., malignant vs. benign), and (2) identify specific genes that play a role in determining those categories. Here we present a novel and simple method that exhaustively scans microarray data for unambiguous gene expression patterns. Such patterns of data can be used as the basis for classification into biological or clinical categories. The method, termed the Characteristic Attribute Organization System (CAOS), is derived from fundamental precepts in systemati...

• Type: Journal
• Year: 2002
• Where: JBI
• Authors: Indra Neil Sarkar, Paul J. Planet, T. E. Bael, S. E. Stanley, Mark Siddall, Robert DeSalle, David H. Figurski
• Keywords: Bioinformatics, Gene Expression Microarray, JBI 2002, Microarray Data, Specific Genes