GA Generates New Amino Acid Indices through Comparison between Native and Random Sequences

スポンサーリンク

概要

• 論文の詳細を見る

• The amino acid sequence of a protein carries its folding information. If the information is encoded by the arrangement of the amino acid residues along the primary structure, the random shuffling of the residues would degrade the information. We developed a new method to compare the native sequence with random sequences generated from the native sequence, in order to extract such information. First, amino acid indices were randomly generated. That is, the initial indices have no significance on the feature of residues. Next, using the indices, the averaged distance between a native sequence and the random sequences was calculated, based on the autoregressive(AR)analysis and the linear predictive coding(LPC)cepstrum analysis. The indices were subjected to the genetic algorithm(GA)using the distance as the fitness, so that the distance between the native sequence and the random sequences becomes larger. We found that the indices converged to hydrophobicity indices by the GA operation. The AR analysis with the converged indices revealed that the autocorrelation in the native sequence is related to the secondary structure.

• 一般社団法人情報処理学会の論文
• 2000-11-15

著者

• Kanai S

  Department Of Bioinformatics Biomolecular Engineering Research Institute:(present Address)parmadesig

• Toh Hiroyuki

  Department Of Bioinformatics Biomolecular Engineering Research Institute

• Kanai Satoru

  Department Of Bioinformatics Biomolecular Engineering Research Institute:(present Address)parmadesig

関連論文

• Effect of Granulocyte Colony-Stimulating Factor on Bone Metabolism during Peripheral Blood Stem Cell Mobilization
• GA Generates New Amino Acid Indices through Comparison between Native and Random Sequences
• Reverse Transcriptase-containing DNA Viruses and Plasmids Lack Integrase

スポンサーリンク