Comparative Computational Approach for Evaluating Transposon Detection in Genomic Data.

Transposable elements, commonly referred to as transposons, are DNA sequences with the ability to change their position within a genome. This mobility can have significant consequences on the structure, function, and evolution of the overall genome architecture [1]. Due to their substantial impact on gene regulation and genetic disease development, transposons have been extensively researched. Consequently, accurately identifying and mapping transposons is crucial for understanding their biological ramifications. Over the years, numerous computational tools have been developed to detect and characterize transposons in genomic sequences, albeit their performance can differ based on input sequence characteristics and underlying algorithms [2]. Among these tools, Target / Integrative Genetic Element Retriever (TIGER) can precisely identify transposes-encoding mobile DNAs in a given genome [3]. The aim of the current study is to discover transposons using TIGER in E. coli genomes and validate them through comparative genomics with published databases. In this work, we will discuss the implications of our findings within the bioinformatics community, emphasizing the accuracy and effectiveness of TIGER in transposon discovery. We will pinpoint the limitations of our research, adjust the program, and consider potential applications for comparing different bioinformatics tools while incorporating user-specified parameters. Our research contributes to the ongoing enhancement of methods for detecting transposons by offering critical insights about the performance of TIGER and BLAST in comparison.