Skip to main navigation Skip to search Skip to main content

Discrimination of Thermophilic Proteins and Non-thermophilic Proteins Using Feature Dimension Reduction

  • Zifan Guo
  • , Pingping Wang
  • , Zhendong Liu*
  • , Yuming Zhao*
  • *Corresponding author for this work
  • University of Electronic Science and Technology of China
  • School of Life Science and Technology, Harbin Institute of Technology
  • Shandong Jianzhu University
  • Northeast Forestry University

Research output: Contribution to journalArticlepeer-review

Abstract

Thermophilicity is a very important property of proteins, as it sometimes determines denaturation and cell death. Thus, methods for predicting thermophilic proteins and non-thermophilic proteins are of interest and can contribute to the design and engineering of proteins. In this article, we describe the use of feature dimension reduction technology and LIBSVM to identify thermophilic proteins. The highest accuracy obtained by cross-validation was 96.02% with 119 parameters. When using only 16 features, we obtained an accuracy of 93.33%. We discuss the importance of the different characteristics in identification and report a comparison of the performance of support vector machine to that of other methods.

Original languageEnglish
Article number584807
JournalFrontiers in Bioengineering and Biotechnology
Volume8
DOIs
StatePublished - 22 Oct 2020
Externally publishedYes

Keywords

  • amino acid
  • feature dimension reduction
  • feature selection
  • support vector machine
  • thermophilic proteins

Fingerprint

Dive into the research topics of 'Discrimination of Thermophilic Proteins and Non-thermophilic Proteins Using Feature Dimension Reduction'. Together they form a unique fingerprint.

Cite this