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Related Concept Videos

Molecular Structure and Acidity02:34

Molecular Structure and Acidity

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An acid can be deprotonated to form a conjugate base or an anion. If the produced anion is more stable, then the acid is stronger. On the contrary, if the anion is unstable, then the acid is weaker. Hence, to determine the acidity of the compound, the stability of its conjugate base is studied using various factors.
The size effect explains the change in atomic size on acidity. When comparing the acids formed from elements that belong to the same column in the periodic table, their atomic sizes...
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Protein Networks02:26

Protein Networks

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Acid Strength and Molecular Structure03:05

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Binary Acids and Bases
In the absence of any leveling effect, the acid strength of binary compounds of hydrogen with nonmetals (A) increases as the H-A bond strength decreases down a group in the periodic table. For group 17, the order of increasing acidity is HF < HCl < HBr < HI. Likewise, for group 16, the order of increasing acid strength is H2O < H2S < H2Se < H2Te. Across a row in the periodic table, the acid strength of binary hydrogen compounds increases with increasing...
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Lewis Structures of Molecular Compounds and Polyatomic Ions02:54

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To draw Lewis structures for complicated molecules and molecular ions, it is helpful to follow a step-by-step procedure as outlined:
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Structure of Benzene: Molecular Orbital Model01:18

Structure of Benzene: Molecular Orbital Model

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According to the molecular orbital (MO) model, benzene has a planar structure with a regular hexagon of six sp2 hybridized carbons. As shown in Figure 1, each carbon is bonded to three other atoms with C–C–C and H–C–C bond angles of 120°. The C–H bond length is 109 pm, and the C–C bond length is 139 pm which is midway between the single bond length of sp3 hybridized carbons (154 pm) and sp2 hybridized carbons (133 pm).
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Molecular and Ionic Solids02:54

Molecular and Ionic Solids

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Crystalline solids are divided into four types: molecular, ionic, metallic, and covalent network based on the type of constituent units and their interparticle interactions.
Molecular Solids
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Related Experiment Video

Updated: Jan 20, 2026

A Gut-on-a-Chip Model to Study the Gut Microbiome-Nervous System Axis
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The Human Gut Microbiome is Structured to Optimize Molecular Interaction Networks.

Yiwei Ling1, Yu Watanabe1, Shujiro Okuda1

  • 1Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata 951-8510, Japan.

Computational and Structural Biotechnology Journal
|August 28, 2019
PubMed
Summary

This study introduces a bioinformatics method to predict bacterial interactions in the human gut microbiome. The approach identifies gene pairs involved in interspecies communication, revealing organized interaction networks.

Keywords:
Human gutIGC, Integrated reference catalog of the human gut microbiomeInterspecific interactionKO, KEGG OrthologyMetagenomicsMicrobiomeMolecular interaction networks

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Systems Biology

Background:

  • Estimating in situ bacterial functions from microbiome data is common, but predicting interspecies interaction networks remains a significant challenge.
  • Understanding these interactions is crucial for deciphering the complex dynamics of the human gut microbiome.

Purpose of the Study:

  • To develop a novel bioinformatics method for predicting bacterial interspecies interaction networks using human gut metagenome data.
  • To identify molecular signatures indicative of functional interactions between bacterial species within the gut environment.

Main Methods:

  • Utilized bioinformatics approaches to analyze human gut metagenome data.
  • Focused on identifying adjacent gene pairs encoding membrane proteins and involved in metabolic pathway interactions.
  • Compared interaction gene pairs in actual metagenome data against random simulated datasets.

Main Results:

  • The proposed method identified specific gene pairs at boundary regions, encoding membrane proteins (e.g., transporters, channel proteins) crucial for interspecies interactions.
  • Actual human gut metagenome data showed significantly more reliable interspecies interaction gene pairs than simulated data.
  • Demonstrated that microbiome species composition supports robust interspecific interactions.

Conclusions:

  • Molecular interaction networks in the human gut flora are structured by a combination of universal and group-specific interaction patterns.
  • The developed method provides a reliable way to infer bacterial interactions from metagenomic data, advancing microbiome research.