Assessing protein similarity with Gene Ontology and its use in subnuclear localization prediction

Background: The accomplishment of the various genome sequencing projects resulted in accumulation of massive amount of gene sequence information. This calls for a large-scale computational method for predicting protein localization from sequence. The protein localization can provide valuable information about its molecular function, as well as the biological pathway in which it participates. The prediction of localization of a protein at subnuclear level is a challenging task. In our previous work we proposed an SVM-based system using protein sequence information for this prediction task. In this work, we assess protein similarity with Gene Ontology (GO) and then improve the performance of the system by adding a module of nearest neighbor classifier using a similarity measure derived from the GO annotation terms for protein sequences. Results: The performance of the new system proposed here was compared with our previous system using a set of proteins resided within 6 localizations co...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Zhengdeng Lei, Yang Dai
• Keywords: BMCBI 2006, Protein, Protein Localization, Sequence Information