Performance analysis of support vector machine combined with global encoding on detection of protein-protein interaction network of HIV virus

Dian Lestari, S. Aprilia, Alhadi B.

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Proteins are bio-macromolecules that have an important role in living organisms. This type of protein consists of a series of combinations of 20 amino acids. In living organisms, Protein-Protein Interactions (PPIs) have an important role in most biological processes so that by detecting protein interactions (PPIs) will be able to understand molecular mechanisms in biological systems. By using the calculation process and applying machine learning method, it will be more efficient than the experimental method that takes a long time and expensive cost. The novelty in this paper we use the Support Vector Machine (SVM) combined with Global Encoding (GE) to achieve better performance than previous methods and the dataset used is the interaction of HIV proteins with humans based on the sequence of amino acids. The results show that the proposed method is robust, feasible and can be used in detecting interactions of other proteins with an accuracy of up to 85 %.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017
EditorsRatna Yuniati, Terry Mart, Ivandini T. Anggraningrum, Djoko Triyono, Kiki A. Sugeng
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735417410
DOIs
Publication statusPublished - 22 Oct 2018
Event3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017 - Bali, Indonesia
Duration: 26 Jul 201727 Jul 2017

Publication series

NameAIP Conference Proceedings
Volume2023
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017
Country/TerritoryIndonesia
CityBali
Period26/07/1727/07/17

Keywords

  • Global Encoding
  • HIV Virus
  • Protein-Protein Interaction
  • Support Vector Machine

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