Three dimensional representation of amino acid characteristics

Sezerman O. U., Islamaj R., Alpaydin E.

23rd Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, İstanbul, Türkiye, 25 - 28 Ekim 2001, cilt.23, ss.2903-2906 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 23
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.2903-2906
  • Anahtar Kelimeler: substitution matrices, machine learning, distance mapping, SUBSTITUTION MATRICES
  • Acıbadem Mehmet Ali Aydınlar Üniversitesi Adresli: Hayır

Özet

Amino acid substitution matrices which shows the similarity scores between pairs of amino acids have been widely used in protein sequence alignments. These matrices are based on the Dayhoff model of evolutionary substitution rates. Using machine learning techniques we obtained three dimensional representations of these matrices while preserving most of the information obtained in the matrices. Vector representation of amino acids has many applications in pattern recognition.