Abstract
The prediction of protein subcellular localization (SCL) has been a long-running challenge in bioinformatics. Protein SCL is crucial for a protein to exercise its functions properly. The reliance of protein localization on signaling peptides and the information available in gene ontology (GO) databases makes it possible to use computational approaches to predict protein SCL. SCL methods can be classified as either sequence-based or annotation-based. Machine learning algorithms and classifiers are used in protein SCL prediction tools. This review presents a list of protein SCL predictors published in the last 5 years.
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