Go molecular function terms are predictive of subcellular localization.
A protein's function is closely linked to its subcellular localization. Use of Gene Ontology (GO) molecular function terms to extend sequence-based subcellular localization prediction has been previously shown to improve predictive performance. Here, we explore directly the relationship between GO function annotations and localization information, identifying both highly predictive single terms, and terms with large information gain with respect to location. The results identify a number of predictive and informative GO terms with respect to subcellular location, particularly nucleus, extracellular space, membrane, mitochondrion, endoplasmic reticulum and Golgi. There are several clear examples illustrating why the addition of function information provides additional predictive power over sequence alone. Other interesting phenomena can also be seen in the results. Most predictive or informative terms are imperfect, and incorrect prediction may often call out significant biological phenomena. Finally, these results may be useful in the GO annotation process.
Lu
Z
Z
Center for Computational Pharmacology, University of Colorado Health Sciences Centre, School of Medicine, Denver, CO, USA.
Hunter
L
L
D000595:Amino Acid Sequence; D000818:Animals; D019295:Computational Biology; D030562:Databases, Protein; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D013347:Subcellular Fractions / Q000737:chemistry*; D018875:Vocabulary, Controlled
D011506:Proteins