Prediction of Thermophilic Protein with Pseudo Amino Acid Composition: An Approach from Combined Feature Selection and Reduction

$63.10 plus tax (Refund Policy)

Buy Article:

Abstract:

Prediction of thermophilic and mesophilic protein plays a crucial role in both biochemistry and bioengineering. In this study, a different mode of pseudo amino acid composition (PseAAC) was proposed to formulate the protein samples by integrating the amino acid composition, the physic chemical features, as well as the composition transition and distribution features, where each of the protein samples was represented by a numerical vector through the sequencebased approach. Using the support vector machine algorithm, an accurate and reliable classifier was constructed to predict the thermophilic and mesophilic proteins. Moreover, three feature reduction algorithms were obtained for locating the most vital features and reducing the size of feature space. Among the three feature reduction algorithms, the genetic algorithm performed best. Finally, with the reduced features extracted from the genetic algorithm, it was observed that for the selected dataset the new classifier achieved a high accuracy of 95.93% with the Matthews correlation coefficient of 0.9187.





Keywords: Amino acid composition; classifier; feature reduction; genetic algorithm; support vector machine

Document Type: Research Article

DOI: http://dx.doi.org/10.2174/092986611795446085

Publication date: July 1, 2011

More about this publication?
  • Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.
Related content

Tools

Favourites

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect 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