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Related Concept Videos

Integrins01:10

Integrins

Animal and protozoan cells do not have cell walls to help maintain shape and provide structural stability. Instead, these eukaryotic cells secrete a sticky mass of carbohydrates and proteins into the spaces between adjacent cells. This network of proteins and molecules is called an extracellular matrix or ECM.
Some ECM proteins assemble into a basement membrane to which the remaining components adhere. Proteoglycans typically form the bulk of the ECM while fibrous proteins, like collagen,...
Activation of Integrins01:15

Activation of Integrins

Integrins bind ligands and transmit information from outside the cell to inside or vice-versa through an "outside-in signaling" or "inside-out signaling."
In "outside-in signaling," external factors in the extracellular space bind to exposed ligand binding sites on integrins. This causes the inactive protein to undergo a conformational change to become active. Integrins are often clustered on the cell membrane. Repetitive and regularly spaced ligand binding events provide an effective stimulus.
Intracellular Signaling Affects Focal Adhesions01:17

Intracellular Signaling Affects Focal Adhesions

Integrins act both as extracellular input receivers and as intracellular processing activators. As their name suggests, integrins are entirely integrated into the membrane structure. Their hydrophobic membrane-spanning regions interact with the phospholipid bilayer's hydrophobic region. These membrane receptors provide extracellular attachment sites for effectors like hormones and growth factors. They activate intracellular response cascades when their effectors are bound and active.
Some...
Intralumenal Vesicles and Multivesicular Bodies01:38

Intralumenal Vesicles and Multivesicular Bodies

Intraluminal vesicles (ILVs) are small vesicles 50-80 nm in diameter formed during the maturation of early endosomes. A specialized endosome containing numerous ILVs is called a multivesicular body (MVB). ILVs contain internalized molecules such as antigens, nucleic acids, proteins, and metabolites. Some of these molecules are released from the MVBs inside exosomes and are transported to other cells. Other MVBs contain molecules that are retained in the ILVs and are later degraded within the...
The Intrinsic Apoptotic Pathway01:31

The Intrinsic Apoptotic Pathway

Internal cellular stress, such as cellular injury or hypoxia, triggers intrinsic apoptosis. The B-cell lymphoma 2 (Bcl-2) family of proteins are the primary regulators of the intrinsic apoptotic pathway. For example, during DNA damage, checkpoint proteins, such as Ataxia Telangiectasia Mutated (ATM protein) and Checkpoints Factor-2 (Chk2) proteins, are activated. These proteins phosphorylate p53 which further activates pro-apoptotic proteins, such as Bax, Bak, PUMA, and Noxa, and inhibits...
Protein Transport into the Inner Mitochondrial Membrane01:34

Protein Transport into the Inner Mitochondrial Membrane

Nuclear encoded mitochondrial precursors are imported to the inner membrane in a multistep process involving two separate translocons, TIM22 and TIM23. TIM23 is a cation-selective pore that remains closed by the N terminal segment of the protein. Negative charges on the TIM23 act as a receptor for the incoming precursor, pulling the positively charged matrix-targeting sequence for peptide insertion and translocation.
Transport of mitochondrial precursors across the TIM23 channel is driven by...

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Related Experiment Video

Updated: Jun 26, 2026

Assembly and Purification of Prototype Foamy Virus Intasomes
10:20

Assembly and Purification of Prototype Foamy Virus Intasomes

Published on: March 19, 2018

Beyond clinical phenotype: the biologic integratome.

David Grimaldi1, Yann-Erick Claessens, Jean-Paul Mira

  • 1Department of Critical Care Medicine, AP-HP, Hopital Cochin, University Paris Descartes, Paris, France.

Critical Care Medicine
|December 24, 2008
PubMed
Summary

Network analysis of complex biological data offers new insights into disease mechanisms. This approach helps identify therapeutic targets by understanding molecular interactions and genetic factors influencing disease phenotypes.

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In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

Area of Science:

  • Biomedical Research
  • Systems Biology
  • Computational Biology

Background:

  • Current disease classification relies on observational correlations, limiting understanding of molecular drivers in critical illnesses.
  • Diseases often stem from complex physiological process disruptions involving multiple control loops, pharmacologic agents, and environmental factors.
  • High-throughput technologies like whole-genome sequencing generate vast 'omics' datasets, presenting interpretation challenges.

Purpose of the Study:

  • To address the challenge of interpreting large biological datasets for fundamental and applied biological information.
  • To apply network analysis to biological problems for a deeper mechanistic understanding of disease.
  • To identify factors influencing disease phenotype and therapeutic targets through network analysis.

Main Methods:

  • Utilizing 'omics' data sets describing cellular biomolecules.
  • Applying network analysis to the biological integratome.
  • Analyzing genetic and environmental factors governing intermediate phenotypes.

Main Results:

  • Network analysis provides unique insights into disease mechanisms by identifying factors influencing disease phenotype.
  • It offers a mechanistic basis for defining phenotypic differences based on genetic and environmental influences.
  • The approach successfully identifies potential therapeutic targets capable of altering disease expression.

Conclusions:

  • Network analysis is a powerful tool for interpreting complex biological data and understanding disease mechanisms.
  • It facilitates the identification of novel therapeutic targets by elucidating molecular interactions and contributing factors.
  • This approach moves beyond simple data aggregation to provide a systems-level understanding of disease.