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Related Concept Videos

Antibody Structure01:10

Antibody Structure

Overview
Antibodies, also known as immunoglobulins (Ig), are essential players of the adaptive immune system. These antigen-binding proteins are produced by B cells and make up 20 percent of the total blood plasma by weight. In mammals, antibodies fall into five different classes, which each elicits a different biological response upon antigen binding.
The Y-Shaped Structure of Antibodies Consists of Four Polypeptide Chains
Antibodies consist of four polypeptide chains: two identical heavy...
Antibody Structure01:10

Antibody Structure

Overview
Antibodies, also known as immunoglobulins (Ig), are essential players of the adaptive immune system. These antigen-binding proteins are produced by B cells and make up 20 percent of the total blood plasma by weight. In mammals, antibodies fall into five different classes, which each elicits a different biological response upon antigen binding.
The Y-Shaped Structure of Antibodies Consists of Four Polypeptide Chains
Antibodies consist of four polypeptide chains: two identical heavy...
Antibody Structure and Classes01:25

Antibody Structure and Classes

Antibodies, also known as immunoglobulins, are produced by B cells in response to foreign substances, such as bacteria and viruses. These proteins are critical for recognizing and neutralizing these substances, protecting the body from potential harm.
The basic structure of an antibody consists of four protein chains: two identical heavy chains and two identical light chains. These chains are held together by disulfide bonds and other non-covalent interactions, forming a Y-shaped structure.
Diversity of Antigen Receptors01:28

Diversity of Antigen Receptors

Antigen receptors are essential components of the immune system crucial in defending the body against foreign invaders. These receptors are present on the surface of B and T cells, enabling them to recognize antigens and mount an appropriate immune response.
Before encountering any antigen, lymphocytes express these receptors. On B cells, the antigen receptor is a membrane-bound antibody molecule called BCR; on T cells, it is a T cell receptor or TCR. B and T cell receptors are composed of two...
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...
Antibody Actions01:26

Antibody Actions

Antibodies, or immunoglobulins, are critical players in the immune system's arsenal against invading pathogens. Produced by B cells and plasma cells, their primary role is to detect and bind to specific antigens, molecules found on the surface of pathogens like bacteria or viruses. Beyond antigen recognition, antibodies perform several vital functions that contribute to immune defense.
Neutralization
Antibodies can bind to pathogens, preventing them from infecting host cells. This process...

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Related Experiment Video

Updated: Jun 13, 2026

Studying Protein Function and the Role of Altered Protein Expression by Antibody Interference and Three-dimensional Reconstructions
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Studying Protein Function and the Role of Altered Protein Expression by Antibody Interference and Three-dimensional Reconstructions

Published on: April 21, 2016

Modularity and anti-modularity in networks with arbitrary degree distribution.

Arend Hintze1, Christoph Adami

  • 1Keck Graduate Institute of Applied Life Sciences, 535 Watson Drive, Claremont, CA 91711, USA. ahintze@kgi.edu

Biology Direct
|May 13, 2010
PubMed
Summary

We developed a model to grow networks with specific properties, creating useful surrogates for biological and technological systems. Network features often arise from growth processes, not just function.

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Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library
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Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library

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Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing
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Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

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Related Experiment Videos

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Studying Protein Function and the Role of Altered Protein Expression by Antibody Interference and Three-dimensional Reconstructions
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Studying Protein Function and the Role of Altered Protein Expression by Antibody Interference and Three-dimensional Reconstructions

Published on: April 21, 2016

Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library
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Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library

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Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing
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Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

Published on: March 15, 2019

Area of Science:

  • Systems biology
  • Network science
  • Computational biology

Background:

  • Analyzing network properties is crucial for understanding systems biology, social networks, and infrastructure.
  • Obtaining systematic controls for real-world networks is challenging due to inherent functional constraints.

Purpose of the Study:

  • To present an algorithmic model for generating networks with tunable degree distributions and modularity.
  • To create artificial network surrogates for studying biological and technological systems.
  • To investigate how network growth parameters influence topological and functional properties.

Main Methods:

  • Developed an algorithmic model using a small set of parameters to grow networks.
  • Utilized an assortativity matrix to specify network connectivity.
  • Investigated control of degree distribution via node/edge addition and duplication probabilities.
  • Analyzed modularity, anti-modularity, path length, correlation, small-world-ness, and phase transitions.

Main Results:

  • Successfully grew networks with a wide range of biologically and technologically relevant degree distributions and modularity.
  • Demonstrated that degree distribution is primarily controlled by node/edge addition and duplication probabilities.
  • Introduced and analyzed the concept of anti-modularity.
  • Observed that global network properties are dependent on growth parameters.

Conclusions:

  • Growing networks with specified characteristics enables the creation of functional surrogates for biological and technological systems.
  • Hypotheses regarding network formation can be tested using this growth model.
  • Many observed network properties may be artifacts of the growth process rather than functional necessities.