2005 | OriginalPaper | Buchkapitel
Protein Secondary Structure Prediction Using Sequence Profile and Conserved Domain Profile
verfasst von : Seon-Kyung Woo, Chang-Beom Park, Seong-Whan Lee
Erschienen in: Advances in Intelligent Computing
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper, we proposed a novel method for protein secondary structure prediction using sequence profile and conserved domain profile. Sequence profile generated from PSI-BLAST (position specific iterated BLAST) has been widely used in protein secondary structure prediction, because PSI-BLAST shows good performance in finding remote homology. Conserved domains kept functional and structural information of related proteins; therefore we could draw remote homology information in conserved domains using RPS-BLAST (reverse position specific BLAST). We combined sequence profile and conserved domain profile to get more remote homology information, and propose a method which used the combined profile to predict the protein secondary structures. In order to verify the effectiveness of our proposed method, we implemented a protein secondary structure prediction system. Overall prediction accuracy reached 75.9% on the RS126 data set. The improvement by incorporating conserved domain information exceeded 3%, and this result showed that our proposed method could improve significantly the accuracy of protein secondary structure prediction.