Rearrangement Distance Problems: An updated survey

IF 23.8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS ACM Computing Surveys Pub Date : 2024-03-20 DOI:10.1145/3653295
Andre Rodrigues Oliveira, Klairton Lima Brito, Alexsandro Oliveira Alexandrino, Gabriel Siqueira, Ulisses Dias, Zanoni Dias
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Abstract

One of the challenges in the Comparative Genomics field is to infer how close two organisms are based on the similarities and differences between their genetic materials. Recent advances in DNA sequencing have made complete genomes increasingly available. That said, several new algorithms trying to infer the distance between two organisms based on genome rearrangements have been proposed in the literature. However, given the diversity of approaches, the diversity of genome rearrangement events, or even how each work models the genomes and what assumptions are made by each of them, finding the ideal algorithm for each situation or simply knowing the range of applicable approaches can be challenging. In this work, we review these approaches having the algorithmic and combinatorial advances since 2010 as our main focus. This survey aims to organize the recently published papers using a concise notation and to indicate the gaps filled by each of them in the literature. This makes it easier to understand what still needs to be done and what has room for enhancement.

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重排距离问题:最新调查
比较基因组学领域的挑战之一是根据两种生物遗传物质的异同来推断它们之间的亲缘关系。最近,DNA 测序技术的进步使得越来越多的人可以获得完整的基因组。因此,文献中提出了几种新算法,试图根据基因组重排来推断两种生物之间的距离。然而,由于方法的多样性、基因组重排事件的多样性,甚至每种方法是如何建立基因组模型的,以及每种方法都做了哪些假设,因此要为每种情况找到理想的算法,或者仅仅了解适用方法的范围都具有挑战性。在这项工作中,我们以 2010 年以来的算法和组合进展为重点,对这些方法进行了回顾。本调查旨在使用简洁的符号组织近期发表的论文,并指出每篇论文在文献中填补的空白。这样,我们就能更容易地了解哪些方面还有待改进,哪些方面还有提升的空间。
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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