A Novel Three-Stage Filter-Wrapper Framework for miRNA Subset Selection in Cancer Classification

Informatics

卷:5

Mohammad Bagher Dowlatshahi¹  Vali Derhami²  Hossein Nezamabadi-pour³ 

[1] Department of Computer Engineering, Faculty of Engineering, Lorestan University, Khoramabad 1489684511, Iran;

[2] Department of Computer Engineering, Faculty of Engineering, Yazd University, Yazd 891581-8411, Iran;

[3] Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman 76169-14111, Iran;

关键词: miRNA subset selection;    hybrid filter-wrapper;    three-stage framework;    high-dimensionality;    Competitive Swarm Optimization;    cancer classification;   

DOI  :  10.3390/informatics5010013

来源: DOAJ

【 摘 要 】

Micro-Ribonucleic Acids (miRNAs) are small non-coding Ribonucleic Acid (RNA) molecules that play an important role in the cancer growth. There are a lot of miRNAs in the human body and not all of them are responsible for cancer growth. Therefore, there is a need to propose the novel miRNA subset selection algorithms to remove irrelevant and redundant miRNAs and find miRNAs responsible for cancer development. This paper tries to propose a novel three-stage miRNAs subset selection framework for increasing the cancer classification accuracy. In the first stage, multiple filter algorithms are used for ranking the miRNAs according to their relevance with the class label, and then generating a miRNA pool obtained based on the top-ranked miRNAs of each filter algorithm. In the second stage, we first rank the miRNAs of the miRNA pool by multiple filter algorithms and then this ranking is used to weight the probability of selecting each miRNA. In the third stage, Competitive Swarm Optimization (CSO) tries to find an optimal subset from the weighed miRNAs of the miRNA pool, which give us the most information about the cancer patients. It should be noted that the balance between exploration and exploitation in the proposed algorithm is accomplished by a zero-order Fuzzy Inference System (FIS). Experiments on several miRNA cancer datasets indicate that the proposed three-stage framework has a great performance in terms of both the low error rate of the cancer classification and minimizing the number of miRNAs.

【 授权许可】

Unknown