The distance-profile representation and its application to detection of distantly related protein families

Background: Detecting homology between remotely related protein families is an important problem in computational biology since the biological properties of uncharacterized proteins can often be inferred from those of homologous proteins. Many existing approaches address this problem by measuring the similarity between proteins through sequence or structural alignment. However, these methods do not exploit collective aspects of the protein space and the computed scores are often noisy and frequently fail to recognize distantly related protein families. Results: We describe an algorithm that improves over the state of the art in homology detection by utilizing global information on the proximity of entities in the protein space. Our method relies on a vectorial representation of proteins and protein families and uses structure-specific association measures between proteins and template structures to form a high-dimensional feature vector for each query protein. These vectors are then p...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Chin-Jen Ku, Golan Yona
• Keywords: BMCBI 2005, Protein, Protein Families, Related Protein Families