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Related Concept Videos

Skewness01:06

Skewness

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The measures of central tendency calculated from a data set may not reveal much about its intrinsic distribution. If a plot is made of the data set’s values, the mean and the median may not only differ, but also the plot may have more values on one side of the central tendencies. Such a data set is said to be skewed towards that side.
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If the frequency distribution of a data set is more inclined towards smaller or larger values, the distribution is said to be skewed. If data values are skewed to the right, then the distribution is called positively skewed. Conversely, if the plot is skewed to the left, the distribution is called negatively skewed.
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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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Matter: Pure Substances and Mixtures
According to its composition, the matter can be classified into two broad categories — pure substances and mixtures. 
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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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As a system undergoes a change, its internal energy can change, and energy can be transferred from the system to the surroundings, or from the surroundings to the system.
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Updated: Feb 7, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Novel metrics for quantifying bacterial genome composition skews.

Lena M Joesch-Cohen1,2, Max Robinson1, Neda Jabbari1

  • 1Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.

BMC Genomics
|July 13, 2018
PubMed
Summary

Novel metrics reveal bacterial genome composition skews, offering insights into evolutionary constraints. These tools analyze even unfinished genomes, identifying unusual species with shared lifestyles like intracellularity.

Keywords:
Compositional biasGenome metricsLagging strandLeading strandLyme diseaseNucleotide skewObligate intracellular

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Area of Science:

  • Genomics
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Bacterial genomes exhibit compositional skews, differences in nucleotide frequency between DNA strands.
  • These asymmetries are hypothesized to result from mutational biases and selective pressures, such as energy efficiency.
  • Studying these skews requires complete and annotated genomic sequences for comparative analysis.

Purpose of the Study:

  • To develop novel metrics for analyzing bacterial genome composition skews.
  • To enable the analysis of compositional skews in unfinished or partially-annotated genomes.
  • To identify bacterial species with unusual skew patterns and explore their evolutionary implications.

Main Methods:

  • Introduced three novel metrics: dot-skew, cross-skew, and residual skew.
  • Metrics were computed for 7738 bacterial genomes, including partial drafts.
  • Residual skew identifies outliers by comparing observed GC content to a model derived from a genome library.

Main Results:

  • Successfully applied novel metrics to a large dataset of bacterial genomes.
  • Identified outlier species with distinct genome composition skews.
  • Observed that diverse outlier species, including Borrelia and Ehrlichia, share intracellular lifestyles and host-dependent biosynthesis.

Conclusions:

  • Novel metrics effectively capture the influence of host-associated lifestyles and biosynthetic constraints on bacterial genome composition.
  • Identified specific bacterial groups (Borrelia, Ehrlichia, Kinetoplastibacterium, Phytoplasma) with shared skew patterns linked to their lifestyle.
  • Provided accessible software and visualizations for further research on genome composition skews.