Data Mining and Computational Intelligence in Genomics: Methods for Gene Expression Data Analysis

The advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to an enormous progress in life sciences. Among the most important innovations is the microarray technology, which allowed whole genome measurements at transcriptional level. The characteristics of this data include a fair amount of noise and an atypical dimensionality (which makes difficult the use of classic statistics tools ? experimental samples in the order of dozens and measured parameters in thousands or tens of thousands). Therefore, this book presents a series of computational methods and algorithms, capable of extracting valuable biological knowledge from this type of data. Applications of microarrays and subsequent gene expression analysis range from the assignment of functional categories for genes of unknown biological function, to precise and early diagnosis of different tumor malignancies. Besides these, a central goal of computational analysis of gene expression data is the extraction of regulatory knowledge at genetic level that may be used to provide a broader understanding on the functioning of complex cellular systems.