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Related Concept Videos

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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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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In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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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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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Updated: Feb 20, 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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Genome assembly reborn: recent computational challenges.

Mihai Pop1

  • 1Department of Computer Science and the Center for Bioinformatics and Computational Biology at the University of Maryland, College Park, MD 20742, USA. mpop@umd.edu

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|June 2, 2009
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Summary
This summary is machine-generated.

Next-generation sequencing has spurred advances in genome assembly algorithms. This research surveys key approaches and recent developments, particularly for complex metagenomics applications.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Next-generation sequencing (NGS) technologies have driven significant advancements in genomic research.
  • The increasing volume and complexity of NGS data present new computational challenges for genome assembly.
  • The rise of metagenomics necessitates scalable algorithms for analyzing microbial communities.

Purpose of the Study:

  • To provide a comprehensive overview of major algorithmic approaches in genome assembly.
  • To highlight recent developments and innovations in the field of genome assembly.
  • To address the specific computational challenges posed by metagenomic data.

Main Methods:

  • Algorithmic analysis of existing genome assembly methods.
  • Review of recent literature and published genome assemblers.
  • Discussion of computational strategies for metagenomic data.

Main Results:

  • Identification of key algorithmic paradigms for genome assembly.
  • Summary of advancements tailored to NGS data characteristics.
  • Exploration of solutions for assembling complex microbial communities.

Conclusions:

  • Continued research and algorithm development are crucial for keeping pace with sequencing technology.
  • Metagenomics presents unique and demanding computational problems for genome assembly.
  • Understanding current algorithmic approaches is vital for future genomic studies.