Abstract
The rapid advancement of next-generation sequencing (NGS) technologies has necessitated the parallel evolution of bioinformatics tools for efficient and accurate genome assembly. These tools are pivotal for reconstructing genomic sequences from short reads, enabling significant progress in genomics, personalized medicine, and evolutionary studies. This article reviews the recent advances in genome assembly tools, focusing on algorithmic innovations, hybrid assembly approaches, error correction techniques, and scalability for large genomes. It also highlights the integration of machine learning to enhance accuracy and discusses the future challenges in the field. The comprehensive overview aims to support researchers in selecting appropriate tools and methodologies for specific genome assembly projects.
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