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Related Concept Videos

Genomics02:02

Genomics

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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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Evolutionary Relationships through Genome Comparisons02:54

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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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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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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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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Genetic Screens02:46

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
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Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
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Interactive metagenomic visualization in a Web browser.

Brian D Ondov1, Nicholas H Bergman, Adam M Phillippy

  • 1National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA. ondovb@nbacc.net

BMC Bioinformatics
|October 4, 2011
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Summary
This summary is machine-generated.

Krona is a new visualization tool for metagenomic data, offering intuitive exploration of taxonomic and functional abundances with confidence levels. This HTML5/JavaScript application provides interactive, shareable charts for improved bioinformatic analysis.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Metagenomic studies require accurate estimation of taxonomical and functional group abundances.
  • Existing visualization tools often fail to represent hierarchical relationships and prediction confidence effectively.
  • There is a need for tools that can display quantitative hierarchical data and secondary variables in metagenomic analyses.

Purpose of the Study:

  • To introduce Krona, a novel visualization tool for metagenomic data.
  • To enable intuitive exploration of relative abundances and confidences within metagenomic hierarchies.
  • To demonstrate the utility of HTML5 for creating accessible and interactive bioinformatic visualizations.

Main Methods:

  • Krona utilizes a variant of radial, space-filling displays.
  • Parametric coloring and interactive polar-coordinate zooming are employed for enhanced visualization.
  • The tool is implemented in HTML5 and JavaScript for browser-based interactivity.

Main Results:

  • Krona allows for intuitive exploration of relative abundances and confidences in metagenomic classifications.
  • Interactive charts are generated, viewable in any modern web browser without plugins.
  • Charts are independent documents, facilitating easy sharing and integration into web servers.

Conclusions:

  • Krona is a powerful and accessible tool for metagenomic data visualization.
  • Its interactive displays enhance the interpretation of metagenomic analyses.
  • The browser-based nature ensures portability and easy adoption into existing workflows.