Version 1
: Received: 14 July 2021 / Approved: 15 July 2021 / Online: 15 July 2021 (12:03:44 CEST)
How to cite:
Hosseinpoor, M.; Parvin, H. A Multi-Object Simulated Annealing Approach to Identify Likely Functional Genomic Pairs. Preprints2021, 2021070358. https://doi.org/10.20944/preprints202107.0358.v1
Hosseinpoor, M.; Parvin, H. A Multi-Object Simulated Annealing Approach to Identify Likely Functional Genomic Pairs. Preprints 2021, 2021070358. https://doi.org/10.20944/preprints202107.0358.v1
Hosseinpoor, M.; Parvin, H. A Multi-Object Simulated Annealing Approach to Identify Likely Functional Genomic Pairs. Preprints2021, 2021070358. https://doi.org/10.20944/preprints202107.0358.v1
APA Style
Hosseinpoor, M., & Parvin, H. (2021). A Multi-Object Simulated Annealing Approach to Identify Likely Functional Genomic Pairs. Preprints. https://doi.org/10.20944/preprints202107.0358.v1
Chicago/Turabian Style
Hosseinpoor, M. and H. Parvin. 2021 "A Multi-Object Simulated Annealing Approach to Identify Likely Functional Genomic Pairs" Preprints. https://doi.org/10.20944/preprints202107.0358.v1
Abstract
Metaheuristic algorithms have been frequently using to tackle optimization problems, however such algorithms in the analysis of health-related data is not commonly used as developing metaheuristic algorithms that work well on health-related data is a difficult task due to complexity of the health data in particular genomics and epigenetics data. One of the important tasks in genomics is to predict genomic elements that are incorporating together to regulate a disease-related genes. Predicting such elements are important as they can be used to develop a personalized cure. In this study, we present for the first time, a multi-object simulated annealing algorithm to identify enhancer-promoter like interactions from Hi-C (chromosome conformation capture) data. These regulatory elements can potentially play vital roles as promoters and/or enhancers in appearance and exacerbation of the regulation of gene.s To evaluate the efficiency of the proposed method, we applied our proposed method and traditional methods on the Hi-C data from mice and compared together. Our results show that the interacting elements identified by our new method are more likely to be functional. The source code of the method is publicly available.
Keywords
Metaheuristic algorithms; Health data analytics; Multi-object simulated annealing; optimization
Subject
Computer Science and Mathematics, Algebra and Number Theory
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.