MAPS: An integrated system for protein sequence annotation using support vector machine

An Integrated environment for biological data is valuable to the function annotation of protein sequences. In this paper, we present a protein sequence annotation system, named MAPS (Multiple Annotation for Protein Sequences), which provides a mechanism to extract multiple annotations from various types of biological data including SwissProt keywords, InterPro signatures and GO terms. Furthermore, MAPS can automatically eliminate the annotation errors generated by a pre-trained SVM classifier. It assigns an annotation to the protein sequence at question by considering not only a single similar protein but also all similar proteins with the annotation. In other words, we take account of the evolutionary information of the protein of interest to reduce the error annotations inferred from weak sequence similarities and from sequence identities in non-functional segments. The experimental results show that the error annotations can be eliminated effectively while keeping high accuracy for different types of annotations.