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Related Concept Videos

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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
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Updated: Jan 21, 2026

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
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GAAP: A Genome Assembly + Annotation Pipeline.

Jinhwa Kong1, Sun Huh2, Jung-Im Won3

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We developed the Genome Analysis Pipeline (GAAP) to simplify complex whole-genome analysis for researchers. This tool automates de novo assembly and gene annotation, making genomic studies more accessible.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Whole-genome analysis involves de novo assembly and gene annotation without a reference genome.
  • Numerous powerful but complex tools exist, posing challenges for individual researchers in selecting and integrating them.

Purpose of the Study:

  • To develop a Genome Analysis Pipeline (GAAP) for semiautomated, iterative, and high-throughput whole-genome data analysis.
  • To assist non-IT researchers by providing detailed guidance on genomic analysis stages, tools, and databases.

Main Methods:

  • The GAAP pipeline integrates read correction, de novo genome/transcriptome assembly, gene prediction, and functional annotation.
  • It utilizes a range of established bioinformatics tools and databases.
  • A case study of Toxocara canis whole-genome analysis demonstrates the pipeline's practicality.

Main Results:

  • The developed GAAP pipeline facilitates high-throughput genomic analysis.
  • It simplifies the process of de novo assembly and gene annotation.
  • Intermediate results from the Toxocara canis case study showcase the method's effectiveness.

Conclusions:

  • The GAAP pipeline offers a practical solution for researchers needing to perform complex whole-genome analyses.
  • It lowers the barrier to entry for non-bioinformaticians in genomic research.
  • The pipeline supports iterative and semiautomated analysis for efficient data interpretation.