240 Naka Hall
Eukaryotic cells contain diverse subcellular organelles. These organelles form distinct
functional cellular compartments where different biological processes and functions are
carried out. The accurate translocation of a protein is crucial to establish and maintain
cellular organization and function. Newly synthesized proteins are transported to different
cellular components with the assistance of protein transport machineries and complex
targeting signals. Mis-localization of proteins is often associated with metabolic disorders
and diseases. Compared with experimental methods, computational prediction of protein
localization, utilizing different machine learning methods, provides an efficient and
effective way for studying the protein subcellular localization on the whole-proteome level.
Here, we present in this dissertation the bioinformatics methods for studying protein
subcellular localization. We reviewed the studies of protein subcellular transport and
machine learning methods in bioinformatics, presented our work on mitochondrial protein
targeting prediction in plants, summarized the ongoing development of a web-resource for
protein subcellular localization, and discussed the future work and development.