Skip to main content
padlock icon - secure page this page is secure

PSMACA: An Automated Protein Structure Prediction Using MACA (Multiple Attractor Cellular Automata)

Buy Article:

$107.10 + tax (Refund Policy)

Protein Structure Predication from sequences of amino acid has gained a remarkable attention in recent years. Even though there are some prediction techniques addressing this problem, the approximate accuracy in predicting the protein structure is closely 75%. An automated procedure was evolved with MACA (Multiple Attractor Cellular Automata) for predicting the structure of the protein. Most of the existing approaches are sequential which will classify the input into four major classes and these are designed for similar sequences. PSMACA is designed to identify ten classes from the sequences that share twilight zone similarity and identity with the training sequences. This method also predicts three states (helix, strand, and coil) for the structure. Our comprehensive design considers 10 feature selection methods and 4 classifiers to develop MACA (Multiple Attractor Cellular Automata) based classifiers that are build for each of the ten classes. We have tested the proposed classifier with twilight-zone and 1-high-similarity benchmark datasets with over three dozens of modern competing predictors shows that PSMACA provides the best overall accuracy that ranges between 77% and 88.7% depending on the dataset.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics


Document Type: Research Article

Publication date: September 1, 2013

More about this publication?
  • Journal of Bioinformatics and Intelligent Control (JBIC) is an international journal that publishes research articles in areas of the bioinformatics and intelligent control. JBIC is aimed to provide an international forum for the exchange of ideas and new scientific and technological findings to disseminate information and promote the transfer of knowledge between professionals in academia and industry. The journal publishes original research papers; review papers; technical reports and notes; short communications focused on emerging new developments in these research areas.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Aims & Scope
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more