Proteins are distributed to the organelles of the cell by a highly complex sorting machinery. Since experimental localization techniques are time consuming and expensive, various computational techniques to predict the subcellular localization of proteins have been developed. This book describes the biological signals and mechanisms that guide protein localization, and the computational methods employed for localization prediction. The focus is thereby on transmembrane proteins, an important class of proteins that are inserted into the membranes of the cell. Different topological models of transmembrane proteins, utilizing Support Vector Machines, Hidden Markov Models and Conditional Random Fields, are studied and their prediction performances are evaluated. The methods described in this book should be of interest to all researchers working in the field of protein localization prediction.

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