Mutational Slime Mould Algorithm for Gene Selection
A large volume of high-dimensional genetic data has been produced in modern medicine and biology fields. Data-driven decision-making is particularly crucial to clinical practice and relevant procedures. However, high-dimensional data in these fields increase the processing complexity and scale. Iden...
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MDPI AG
2022-08-01
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| Series: | Biomedicines |
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| author | Feng Qiu Pan Zheng Ali Asghar Heidari Guoxi Liang Huiling Chen Faten Khalid Karim Hela Elmannai Haiping Lin |
| author_facet | Feng Qiu Pan Zheng Ali Asghar Heidari Guoxi Liang Huiling Chen Faten Khalid Karim Hela Elmannai Haiping Lin |
| author_sort | Feng Qiu |
| collection | DOAJ |
| description | A large volume of high-dimensional genetic data has been produced in modern medicine and biology fields. Data-driven decision-making is particularly crucial to clinical practice and relevant procedures. However, high-dimensional data in these fields increase the processing complexity and scale. Identifying representative genes and reducing the data’s dimensions is often challenging. The purpose of gene selection is to eliminate irrelevant or redundant features to reduce the computational cost and improve classification accuracy. The wrapper gene selection model is based on a feature set, which can reduce the number of features and improve classification accuracy. This paper proposes a wrapper gene selection method based on the slime mould algorithm (SMA) to solve this problem. SMA is a new algorithm with a lot of application space in the feature selection field. This paper improves the original SMA by combining the Cauchy mutation mechanism with the crossover mutation strategy based on differential evolution (DE). Then, the transfer function converts the continuous optimizer into a binary version to solve the gene selection problem. Firstly, the continuous version of the method, ISMA, is tested on 33 classical continuous optimization problems. Then, the effect of the discrete version, or BISMA, was thoroughly studied by comparing it with other gene selection methods on 14 gene expression datasets. Experimental results show that the continuous version of the algorithm achieves an optimal balance between local exploitation and global search capabilities, and the discrete version of the algorithm has the highest accuracy when selecting the least number of genes. |
| first_indexed | 2024-03-09T04:40:16Z |
| format | Article |
| id | doaj.art-a7af1a0aa1a04a6ea213fbdff57c3ee7 |
| institution | Directory Open Access Journal |
| issn | 2227-9059 |
| language | English |
| last_indexed | 2024-03-09T04:40:16Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomedicines |
| spelling | doaj.art-a7af1a0aa1a04a6ea213fbdff57c3ee72023-12-03T13:22:20ZengMDPI AGBiomedicines2227-90592022-08-01108205210.3390/biomedicines10082052Mutational Slime Mould Algorithm for Gene SelectionFeng Qiu0Pan Zheng1Ali Asghar Heidari2Guoxi Liang3Huiling Chen4Faten Khalid Karim5Hela Elmannai6Haiping Lin7Department of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, ChinaInformation Systems, University of Canterbury, Christchurch 8014, New ZealandDepartment of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, ChinaDepartment of Information Technology, Wenzhou Polytechnic, Wenzhou 325035, ChinaDepartment of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, ChinaDepartment of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaDepartment of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaDepartment of Information Engineering, Hangzhou Vocational & Technical College, Hangzhou 310018, ChinaA large volume of high-dimensional genetic data has been produced in modern medicine and biology fields. Data-driven decision-making is particularly crucial to clinical practice and relevant procedures. However, high-dimensional data in these fields increase the processing complexity and scale. Identifying representative genes and reducing the data’s dimensions is often challenging. The purpose of gene selection is to eliminate irrelevant or redundant features to reduce the computational cost and improve classification accuracy. The wrapper gene selection model is based on a feature set, which can reduce the number of features and improve classification accuracy. This paper proposes a wrapper gene selection method based on the slime mould algorithm (SMA) to solve this problem. SMA is a new algorithm with a lot of application space in the feature selection field. This paper improves the original SMA by combining the Cauchy mutation mechanism with the crossover mutation strategy based on differential evolution (DE). Then, the transfer function converts the continuous optimizer into a binary version to solve the gene selection problem. Firstly, the continuous version of the method, ISMA, is tested on 33 classical continuous optimization problems. Then, the effect of the discrete version, or BISMA, was thoroughly studied by comparing it with other gene selection methods on 14 gene expression datasets. Experimental results show that the continuous version of the algorithm achieves an optimal balance between local exploitation and global search capabilities, and the discrete version of the algorithm has the highest accuracy when selecting the least number of genes.https://www.mdpi.com/2227-9059/10/8/2052gene selectionslime mould algorithmCauchy mutationcrossover and mutationmedical diagnosis |
| spellingShingle | Feng Qiu Pan Zheng Ali Asghar Heidari Guoxi Liang Huiling Chen Faten Khalid Karim Hela Elmannai Haiping Lin Mutational Slime Mould Algorithm for Gene Selection Biomedicines gene selection slime mould algorithm Cauchy mutation crossover and mutation medical diagnosis |
| title | Mutational Slime Mould Algorithm for Gene Selection |
| title_full | Mutational Slime Mould Algorithm for Gene Selection |
| title_fullStr | Mutational Slime Mould Algorithm for Gene Selection |
| title_full_unstemmed | Mutational Slime Mould Algorithm for Gene Selection |
| title_short | Mutational Slime Mould Algorithm for Gene Selection |
| title_sort | mutational slime mould algorithm for gene selection |
| topic | gene selection slime mould algorithm Cauchy mutation crossover and mutation medical diagnosis |
| url | https://www.mdpi.com/2227-9059/10/8/2052 |
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