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Retrotransposons in Plant Genomes: Structure, Identification, and Classification through Bioinformatics and Machine Learning

机译:通过生物信息学和机器学习,植物基因组中的转回转换术:结构,鉴定和分类

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摘要

Transposable elements (TEs) are genomic units able to move within the genome of virtually all organisms. Due to their natural repetitive numbers and their high structural diversity, the identification and classification of TEs remain a challenge in sequenced genomes. Although TEs were initially regarded as “junk DNA”, it has been demonstrated that they play key roles in chromosome structures, gene expression, and regulation, as well as adaptation and evolution. A highly reliable annotation of these elements is, therefore, crucial to better understand genome functions and their evolution. To date, much bioinformatics software has been developed to address TE detection and classification processes, but many problematic aspects remain, such as the reliability, precision, and speed of the analyses. Machine learning and deep learning are algorithms that can make automatic predictions and decisions in a wide variety of scientific applications. They have been tested in bioinformatics and, more specifically for TEs, classification with encouraging results. In this review, we will discuss important aspects of TEs, such as their structure, importance in the evolution and architecture of the host, and their current classifications and nomenclatures. We will also address current methods and their limitations in identifying and classifying TEs.
机译:可转换元素(TES)是能够在几乎所有生物的基因组内移动的基因组单位。由于它们的自然重复数字及其高结构多样性,TES的鉴定和分类仍然是测序基因组的挑战。尽管TES最初被视为“垃圾DNA”,但已经证明它们在染色体结构,基因表达和调节中起关键作用,以及适应和进化。因此,这些元素的高度可靠的注释对于更好地了解基因组功能及其演化至关重要。迄今为止,已经开发出多种生物信息学软件来解决TE检测和分类过程,但仍然存在许多有问题的方面,例如分析的可靠性,精度和速度。机器学习和深度学习是可以在各种科学应用中做出自动预测和决策的算法。它们已经在生物信息学中进行了测试,更具体地用于TES,令人鼓舞的结果分类。在本次审查中,我们将讨论TES的重要方面,例如它们的结构,在主持人的演变和架构中的重要性以及他们当前的分类和命名。我们还将解决当前方法及其限制,以识别和分类TES。

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