Version 1
: Received: 21 May 2024 / Approved: 23 May 2024 / Online: 24 May 2024 (09:27:13 CEST)
How to cite:
Montgomery, R. M. The Real Selfish Gene: Impact of Repetitive Elements on Read Mapping Accuracy, a Simulation Study. Preprints2024, 2024051559. https://doi.org/10.20944/preprints202405.1559.v1
Montgomery, R. M. The Real Selfish Gene: Impact of Repetitive Elements on Read Mapping Accuracy, a Simulation Study. Preprints 2024, 2024051559. https://doi.org/10.20944/preprints202405.1559.v1
Montgomery, R. M. The Real Selfish Gene: Impact of Repetitive Elements on Read Mapping Accuracy, a Simulation Study. Preprints2024, 2024051559. https://doi.org/10.20944/preprints202405.1559.v1
APA Style
Montgomery, R. M. (2024). The Real Selfish Gene: Impact of Repetitive Elements on Read Mapping Accuracy, a Simulation Study. Preprints. https://doi.org/10.20944/preprints202405.1559.v1
Chicago/Turabian Style
Montgomery, R. M. 2024 "The Real Selfish Gene: Impact of Repetitive Elements on Read Mapping Accuracy, a Simulation Study" Preprints. https://doi.org/10.20944/preprints202405.1559.v1
Abstract
Repetitive elements, often referred to as selfish genes, pose significant challenges to genome assembly and read mapping in bioinformatics. These elements can replicate within the genome without providing functional benefits to the host organism, leading to complexities in accurate genome analysis. This study presents a simulation-based approach to illustrate the impact of repetitive elements on read mapping accuracy. By comparing genome sequences with and without repetitive elements, we demonstrate how these selfish genes create ambiguities and errors in read alignment. The findings underscore the importance of developing advanced bioinformatics tools aligned with artificial intelligence to mitigate the effects of repetitive sequences and improve the reliability of genomic analyses.
Computer Science and Mathematics, Mathematical and Computational Biology
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.
