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Related Concept Videos

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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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A dictionary based informational genome analysis.

Alberto Castellini1, Giuditta Franco, Vincenzo Manca

  • 1Department of Computer Science, Strada Le Grazie 15, 37134 Verona, Italy.

BMC Genomics
|September 19, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a novel computational genomics approach using DNA k-mer frequencies to build genomic dictionaries. This method enables a systemic analysis of genomes, aiding in the discovery of biological patterns and genetic networks.

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Area of Science:

  • Computational Genomics
  • Bioinformatics
  • Systems Biology

Background:

  • The post-genomic era necessitates advanced computational methods for genome structure analysis.
  • Alignment-free sequence analysis offers an alternative to traditional methods for biological sequence dissimilarity.
  • Empirical frequencies of DNA k-mers are emerging as a basis for novel genomic analysis.

Purpose of the Study:

  • To develop a systemic approach for analyzing whole genome information.
  • To introduce a methodology based on genomic dictionaries derived from k-mer frequencies.
  • To create an efficient software application for comparative genomics.

Main Methods:

  • Analysis of approximately sixty genomes using informational indexes derived from genomic dictionaries.
  • Computation of informational indexes and frequency distributions for various k-mer dictionary sizes.
  • Development of a software prototype for computing, storing, and visualizing genomic indexes.

Main Results:

  • A systemic view of genomes was achieved, replacing traditional local sequence analysis.
  • Genomic dictionaries and associated informational indexes were successfully computed and analyzed.
  • The software demonstrated effective analysis of genomic repeats and facilitated the definition of synthetic genetic networks.

Conclusions:

  • A novel methodology utilizing genomic dictionaries for comparative genomics was established.
  • An efficient motif-finding software application was developed.
  • The approach holds potential for broader applications in computational genomics, including the discrimination of genomic pathologies.