Data Mining in Bioinformatics (Advanced Information and Knowledge Processing)

8. 1. 1 Protein Subcellular Location The life sciences have entered the post-genome era where the focus of biologicalresearchhasshiftedfromgenomesequencestoproteinfunctionality. Withwhole-genomedraftsofmouseandhumaninhand, scientistsareputting more and more e?ort into obtaining information about the entire proteome in a given cell type. The properties of a protein include its amino acid sequences, its expression levels under various developmental stages and in di?erenttissues, its3Dstructureandactivesites, itsfunctionalandstructural binding partners, and its subcellular location. Protein subcellular location is important for understanding protein function inside the cell. For example, the observation that the product of a gene is localized in mitochondria will support the hypothesis that this protein or gene is involved in energy metabolism. Proteins localized in the cytoskeleton are probably involved in intracellular tra?cking and support. The context of protein functionality is well represented by protein subcellular location. Proteins have various subcellular location patterns [250]. One major category of proteins is synthesized on free ribosomes in the cytoplasm. Soluble proteins remain in the cytoplasm after their synthesis and function as small factories catalyzing cellular metabolites. Other proteins that have a target signal in their sequences are directed to their target organelle (such as mitochondria) via posttranslational transport through the organelle membrane. Nuclear proteins are transferred through pores on the nuclear envelope to the nucleus and mostly function as regulators. The second major category of proteins is synthesized on endoplasmic reticulum(ER)-associated ribosomes and passes through the reticuloendothelial system, consisting of the ER and the Golgi apparatus The goal of this book is to help readers understand state-of-the-art techniques in biological data mining & data management & includes topics such as: * preprocessing tasks such as data cleaning & data integration as applied to biological data * classification & clustering techniques for microarrays * comparison of RNA structures based on string properties & energetics * discovery of the sequence characteristics of different parts of the genome * mining of haplotypes to find disease markers * sequencing of events leading to the folding of a protein * inference of the subcellular location of protein activity * classification of chemical compounds based on structure * special purpose metrics & index structures for phylogenetic applications * a new query language for protein searching based on the shape of proteins * very fast indexing schemes for sequences & pathways Aimed at computer scientists, necessary biology is explained. "The book is aimed at computer scientists, so necessary biology is explained as needed. A glossary provides definitions of critical biological concepts. Finally, problems are provided at the end of several chapters in case readers want to use the book as a text."--Jacket

Written especially for computer scientists, all necessary biology is explained.

Presents new techniques on gene expression data mining, gene mapping for disease detection, and phylogenetic knowledge discovery.

Written especially for computer scientists, all necessary biology is explained. Presents new techniques on gene expression data mining, gene mapping for disease detection, and phylogenetic knowledge discovery.