A signal processing application in genomic research: Protein secondary structure prediction


Aydin Z., Altunbasak Y.

IEEE Signal Processing Magazine, vol.23, no.4, pp.128-131, 2006 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 4
  • Publication Date: 2006
  • Doi Number: 10.1109/msp.2006.1657827
  • Journal Name: IEEE Signal Processing Magazine
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.128-131
  • Abdullah Gül University Affiliated: No

Abstract

Protein structure prediction can be performed at several levels. Secondary structure prediction is concerned with the assignment of each amino acid to a secondary structure state. Prediction of the secondary structure is important as it provides insights into the function of the protein. There are two types of protein secondary prediction algorithms. A single sequence algorithm does not use information about other similar proteins. The algorithm should be suitable for a nonhomologous sequence with no sequence similarity to any other protein sequence. However, prediction accuracy of the algorithm is limited by small size sample. Algorithms of other type explicitly use sequences of homologous proteins, which often have similar structures.