[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 5, Issue 2 (Summer 2018) ::
2018, 5(2): 304-313 Back to browse issues page
Detection and Extraction of Potential Promoter/Enhancer Interactions in Genome of Cancer Patients using an Evolutionary Multi-Objective Algorithm
Mohammadjavad Hosseinpoor , Hamid Parvin , Samad Nejatian , Vahideh Rezaei
Ph.D. in Electrical Engineering, Assistant Professor, Electrical Engineering Dept., Yasooj Branch, Islamic Azad University, Yasooj, Iran
Abstract:   (113 Views)
Introduction: Cancer, as one of the most common diseases, has influenced the health of many people. The main aim of this study was to present a multi-objective evolutionary algorithm. The algorithm is capable of detecting and extracting potentially promoter/enhancer areas in the chromosomes of the affected people using the information concerning inter-genomic interactions. The correct extraction of these areas can help early diagnosis of cancer.
Methods: In this applied and descriptive research, Hi-C data set including information on inter-genomic interactions in the GM12878 cell was used. Multi-objective evolutionary algorithm was used in order to discover and extract potential promoter /enhancer interactions. The mentioned algorithm was implemented using MATLAB software. Furthermore, the efficiency of this algorithm was evaluated using two criteria. The first criterion is a proportional function that calculates the magnitude of inter-genomic interactions relative to the length of the genome regions; and the second criterion is the number of discovered potential promoters/enhancers.
Results: The results and comparisons showed higher efficiency and optimality of the suggested method in discovering promoter/Enhancer interactions with variable length in comparison to HiC-Pro method. Therefore, the suggested method is able to discover the potential promoter/ enhancer interactions that cannot be discovered by HiC-Pro method.
Conclusion: The suggested algorithm is able to optimally discover and extract potential promoter/ enhancer with variable length. This is a great help in medical science for early diagnosis of cancer.
Keywords: Promoter, Enhancer, Hi-C Dataset, Multi-Objective Simulation Annealing Algorithm (MOSA), HiC- Pro Method
Full-Text [PDF 887 kb]   (45 Downloads)    
Type of Study: Original Article | Subject: Bioinformatics
Received: 2017/10/22 | Accepted: 2018/06/12
Send email to the article author

Add your comments about this article
Your username or Email:


XML   Persian Abstract   Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Hosseinpoor M, Parvin H, Nejatian S, Rezaei V. Detection and Extraction of Potential Promoter/Enhancer Interactions in Genome of Cancer Patients using an Evolutionary Multi-Objective Algorithm . Journal of Health and Biomedical Informatics. 2018; 5 (2) :304-313
URL: http://jhbmi.ir/article-1-245-en.html

Volume 5, Issue 2 (Summer 2018) Back to browse issues page
مجله انفورماتیک سلامت و زیست پزشکی Journal of Health and Biomedical Informatics
Persian site map - English site map - Created in 0.05 seconds with 31 queries by YEKTAWEB 3764