Large-scale protein-protein interactions detection by integrating big biosensing data with computational model

Zhu Hong You, Shuai Li, Xin Gao, Xin Luo, Zhen Ji

Research output: Journal article publicationJournal articleAcademic researchpeer-review

35 Citations (Scopus)

Abstract

Protein-protein interactions are the basis of biological functions, and studying these interactions on a molecular level is of crucial importance for understanding the functionality of a living cell. During the past decade, biosensors have emerged as an important tool for the high-throughput identification of proteins and their interactions.However, the high-throughput experimental methods for identifying PPIs are both time-consuming and expensive. On the other hand, high-throughput PPI data are often associated with high false-positive and high false-negative rates. Targeting at these problems, we propose a method for PPI detection by integrating biosensor-based PPI data with a novel computational model. This method was developed based on the algorithm of extreme learning machine combined with a novel representation of protein sequence descriptor. When performed on the large-scale human protein interaction dataset, the proposed method achieved 84.8% prediction accuracy with 84.08% sensitivity at the specificity of 85.53%. We conducted more extensive experiments to compare the proposed method with the state-of-the-art techniques, support vector machine. The achieved results demonstrate that our approach is very promising for detecting new PPIs, and it can be a helpful supplement for biosensor-based PPI data detection.
Original languageEnglish
Article number598129
JournalBioMed Research International
Volume2014
DOIs
Publication statusPublished - 1 Jan 2014

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

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