LAPSE:2019.1139
Published Article
LAPSE:2019.1139
A Review of Computational Methods for Clustering Genes with Similar Biological Functions
Hui Wen Nies, Zalmiyah Zakaria, Mohd Saberi Mohamad, Weng Howe Chan, Nazar Zaki, Richard O. Sinnott, Suhaimi Napis, Pablo Chamoso, Sigeru Omatu, Juan Manuel Corchado
November 24, 2019
Clustering techniques can group genes based on similarity in biological functions. However, the drawback of using clustering techniques is the inability to identify an optimal number of potential clusters beforehand. Several existing optimization techniques can address the issue. Besides, clustering validation can predict the possible number of potential clusters and hence increase the chances of identifying biologically informative genes. This paper reviews and provides examples of existing methods for clustering genes, optimization of the objective function, and clustering validation. Clustering techniques can be categorized into partitioning, hierarchical, grid-based, and density-based techniques. We also highlight the advantages and the disadvantages of each category. To optimize the objective function, here we introduce the swarm intelligence technique and compare the performances of other methods. Moreover, we discuss the differences of measurements between internal and external criteria to validate a cluster quality. We also investigate the performance of several clustering techniques by applying them on a leukemia dataset. The results show that grid-based clustering techniques provide better classification accuracy; however, partitioning clustering techniques are superior in identifying prognostic markers of leukemia. Therefore, this review suggests combining clustering techniques such as CLIQUE and k-means to yield high-quality gene clusters.
Keywords
biological functions detection, gene clustering, informative genes, swarm intelligence
Suggested Citation
Nies HW, Zakaria Z, Mohamad MS, Chan WH, Zaki N, Sinnott RO, Napis S, Chamoso P, Omatu S, Corchado JM. A Review of Computational Methods for Clustering Genes with Similar Biological Functions. (2019). LAPSE:2019.1139
Author Affiliations
Nies HW: School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia
Zakaria Z: School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia
Mohamad MS: Institute for Artificial Intelligence and Big Data, Universiti Malaysia Kelantan, Kota Bharu 16100, Kelantan, Malaysia
Chan WH: School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia
Zaki N: Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirate University, Al Ain 15551, UAE
Sinnott RO: School of Computing and Information Systems, University of Melbourne, Parkville 3010, Victoria, Australia
Napis S: Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Chamoso P: BISITE Research Group, Digital Innovation Hub, University of Salamanca, Edificio I+D+i, C/ Espejos s/n, 37007 Salamanca, Spain [ORCID]
Omatu S: Division of Data-Driven Smart Systems Design, Digital Monozukuri (Manufacturing) Education and Research Center, Hiroshima University, #210, 3-10-31 Kagamiyama, Higashi-Hiroshima 739-0046, Hiroshima Prefecture, Japan
Corchado JM: BISITE Research Group, Digital Innovation Hub, University of Salamanca, Edificio I+D+i, C/ Espejos s/n, 37007 Salamanca, Spain [ORCID]
[Login] to see author email addresses.
Journal Name
Processes
Volume
7
Issue
9
Article Number
E550
Year
2019
Publication Date
2019-08-21
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr7090550, Publication Type: Review
Record Map
Published Article

LAPSE:2019.1139
This Record
External Link

doi:10.3390/pr7090550
Publisher Version
Download
Files
[Download 1v1.pdf] (527 kB)
Nov 24, 2019
Main Article
License
CC BY 4.0
Meta
Record Statistics
Record Views
448
Version History
[v1] (Original Submission)
Nov 24, 2019
 
Verified by curator on
Nov 24, 2019
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2019.1139
 
Original Submitter
Calvin Tsay
Links to Related Works
Directly Related to This Work
Publisher Version