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Related Concept Videos

Spherical Coordinates01:23

Spherical Coordinates

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Spherical coordinate systems are preferred over Cartesian, polar, or cylindrical coordinates for systems with spherical symmetry. For example, to describe the surface of a sphere, Cartesian coordinates require all three coordinates. On the other hand, the spherical coordinate system requires only one parameter: the sphere's radius. As a result, the complicated mathematical calculations become simple. Spherical coordinates are used in science and engineering applications like electric and...
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Gravity between Spherical Bodies01:27

Gravity between Spherical Bodies

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Newton's law of gravitation describes the gravitational force between any two point masses. However, for extended spherical objects like the Earth, the Moon, and other planets, the law holds with an assumption that masses of spherical objects are concentrated at their respective centers.
This assumption can be proved easily by showing that the expression for gravitational potential energy between a hollow sphere of mass (M) and a point mass (m) is the same as it would be for a pair of extended...
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Spherical and Cylindrical Capacitor01:26

Spherical and Cylindrical Capacitor

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A spherical capacitor consists of two concentric conducting spherical shells of radii R1 (inner shell) and R2 (outer shell). The shells have  equal and opposite charges of +Q and −Q, respectively. For an isolated conducting spherical capacitor, the radius of the outer shell can be considered to be infinite.
Conventionally, considering the  symmetry, the electric field between the concentric shells of a spherical capacitor is directed radially outward. The magnitude of the field,...
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Gauss's Law: Spherical Symmetry01:26

Gauss's Law: Spherical Symmetry

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A charge distribution has spherical symmetry if the density of charge depends only on the distance from a point in space and not on the direction. In other words, if the system is rotated, it doesn't look different. For instance, if a sphere of radius R is uniformly charged with charge density ρ0, then the distribution has spherical symmetry. On the other hand, if a sphere of radius R is charged so that the top half of the sphere has a uniform charge density ρ1 and the bottom half has a...
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Gravitation Between Spherically Symmetric Masses01:14

Gravitation Between Spherically Symmetric Masses

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The gravitational potential energy between two spherically symmetric bodies can be calculated from the masses and the distance between the bodies, assuming that the center of mass is concentrated at the respective centers of the bodies.
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Protein Complex Assembly02:41

Protein Complex Assembly

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Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
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Related Experiment Video

Updated: Feb 15, 2026

Metagenomic Analysis of Silage
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Metagenomic Analysis of Silage

Published on: January 13, 2017

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Spherical: an iterative workflow for assembling metagenomic datasets.

Thomas C A Hitch1,2, Christopher J Creevey3

  • 1Institute of Biological, Environmental and Rural Sciences (IBERS), Aberystwyth University, Aberystwyth, Wales, SY23 3FG, UK. thitch@ukaachen.de.

BMC Bioinformatics
|January 25, 2018
PubMed
Summary
This summary is machine-generated.

Metagenomic assembly struggles to incorporate all sequencing data, biasing microbiome analysis. The Spherical workflow iteratively assembles unused reads, significantly increasing utilized data and improving taxonomic profiles for more accurate microbiome insights.

Keywords:
AssemblyGenomicsMetagenome

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Computational Biology

Background:

  • Microbiome studies reveal increasing complexity, necessitating advanced assembly and deep sequencing.
  • Current metagenomic assembly methods often fail to utilize all generated sequence data, leading to biased insights, particularly for minor taxa.
  • This underutilization of sequence information hinders comprehensive understanding of microbial community structure and function.

Purpose of the Study:

  • To address the limitations of current metagenomic assembly techniques in utilizing all sequence data.
  • To develop an effective computational workflow for improved microbiome assembly and analysis.
  • To enhance the accuracy of taxonomic profiling by incorporating previously unutilized sequence reads.

Main Methods:

  • A Python-based iterative workflow named Spherical was developed.
  • The workflow performs successive assembly rounds using unutilized sequencing reads.
  • A 'divide and conquer' strategy allows for efficient assembly of large datasets by processing random subsets.

Main Results:

  • Spherical demonstrated accuracy with simulated data and effectiveness on published metagenomics studies.
  • The workflow increased the amount of utilized reads in assembly by up to 109% compared to standard methods.
  • Significant changes (P < 0.05) in predicted taxonomic profiles were observed due to the additional contigs assembled by Spherical.

Conclusions:

  • Spherical effectively retrieves lost information, improving metagenomic assembly.
  • The workflow enhances the accuracy of taxonomic profiling in microbiome studies.
  • Spherical is freely available, promoting wider adoption in microbial community analysis.