Saada, B.; Estevao, S.; Zhang, J.; Magalhães Muniz, M.M.; Zhang, T. Whole Genome Alignment: Methods, Challenges, and Future Directions. Preprints2024, 2024021197. https://doi.org/10.20944/preprints202402.1197.v1
APA Style
Saada, B., Estevao, S., Zhang, J., Magalhães Muniz, M.M., & Zhang, T. (2024). Whole Genome Alignment: Methods, Challenges, and Future Directions. Preprints. https://doi.org/10.20944/preprints202402.1197.v1
Chicago/Turabian Style
Saada, B., Maria Malane Magalhães Muniz and TianChi Zhang. 2024 "Whole Genome Alignment: Methods, Challenges, and Future Directions" Preprints. https://doi.org/10.20944/preprints202402.1197.v1
Abstract
Whole genome alignment (WGA) is a critical process in comparative genomics, facilitating the detection of genetic variants and aiding our understanding of evolution. This paper offers a detailed overview and categorization of WGA techniques, encompassing suffix tree-based, anchors-based, and graph-based methods. It elaborates on the algorithmic properties of these tools, focusing on performance and methodological aspects. The paper underscores the latest progress in WGA, emphasizing the increasing capacity to manage the growing intricacy and volume of genomic data. However, the field still grapples with computational and biological hurdles affecting the precision and speed of WGA. We explored these challenges and potential future solutions. This paper aims to provide a comprehensive resource for researchers, deepening our understanding of WGA tools and their applications, constraints, and prospects.
Biology and Life Sciences, Biology and Biotechnology
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.
