The Predictor Set Inference in Gene Regulatory Network Using Gravitational Search Algorithm and Mean Conditional Entropy Fitness Measure

Jafari, Mina; Ghavami, Behnam; Sattari Naeini, Vahid

doi:10.22041/ijbme.2017.49393.1155

Document Type : Full Research Paper

Authors

¹ MSc, Computer Engineering Department, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

² Assistant Professor, Computer Engineering Department, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

https://doi.org/10.22041/ijbme.2017.49393.1155

Abstract

The inference of Gene Regulatory Network (GRN) using gene expression data is significantly important in order to understand gene dependencies, regulatory functions among genes, biological processes, way of process occurrence and avoiding some unplanned processes (disease). The accurate inference of GRN needs the accurate inference of predictor set. Generally, the main limitations of the predictor set inference are the small number of samples, the large number of genes and also the possibility influence of noise in gene expression data. Hence, providing efficient methods to infer predictor set with high reliability is a serious need. In this paper, an efficient method is proposed to infer predictor set using Gravitational Search Algorithm (GSA). A GSA is used for each target gene to infer the predictor subset of the gene. In a population, a mass represents a predictor subset of the associated gene. The initial population per target gene is generated by Pearson Correlation Coefficient (PCC). In order to guide the GSA, Mean Conditional Entropy (MCE) is used as the assessment criterion. Experimental results show that the proposed method has a good ability to infer the predictor set with high reliability. In addition, we also compared the proposed algorithm with a recent similar method based on genetic algorithm. Comparison results reveal the advantage of the proposed algorithm on biological datasets with small data volumes and large network scales.

Keywords

Main Subjects

Bioinformatics / Biomedical Informatics / Medical Informatics / Health Informatics

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Iranian Journal of Biomedical Engineering

The Predictor Set Inference in Gene Regulatory Network Using Gravitational Search Algorithm and Mean Conditional Entropy Fitness Measure

References

References

Volume 9, Issue 4
February 2015
Pages 375-386

The Predictor Set Inference in Gene Regulatory Network Using Gravitational Search Algorithm and Mean Conditional Entropy Fitness Measure

References

References

Volume 9, Issue 4February 2015Pages 375-386

Volume 9, Issue 4
February 2015
Pages 375-386