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Related Concept Videos

Autophagy01:27

Autophagy

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Autophagy is a self-digesting process by which a cell protects itself from threats both within and outside the cell, ranging from abnormal proteins to invading bacteria. In this process, obsolete components of the cell and invading microbes are degraded by hydrolytic enzymes active in an acidic environment of the lysosomal lumen.
An autophagic pathway consists of a series of signaling events activated in response to diverse stress and physiological conditions such as food deprivation,...
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Delivery Pathways to the Lysosome01:36

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Eukaryotic cells use different mechanisms to eliminate toxic waste obsolete and worn-out substances. Lysosomes play a pivotal role in this, and hence, these substances are carried to the lysosome from other parts of the cell and extracellular space through different pathways. The most elaborately studied pathways to the lysosome are the endocytic pathways.
Endocytosis
In endocytosis, the cell membrane takes up macromolecules and particles from the surrounding medium. Clathrin-mediated...
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Autophagic Cell Death01:18

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Christian de Duve discovered “autophagy,” a process in which cellular components are engulfed by membrane-bound organelles called autophagosomes. The autophagosomes then fuse with lysosomes to digest the enclosed contents. Autophagy is generally activated in cells to prevent cell death. However, cell death is triggered when the damage is beyond repair.
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PI3K/mTOR/AKT Signaling Pathway01:22

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The mammalian target of rapamycin  (mTOR) is a serine/threonine kinase that regulates growth, proliferation, and cell survival in response to hormones, growth factors, or nutrient availability. This kinase exists in two structurally and functionally distinct forms: mTOR complex 1  (mTORC1) and mTOR complex 2  (mTORC2). The first form (mTORC1) is composed of a rapamycin-sensitive Raptor and proline-rich Akt substrate, PRAS40. In contrast,  mTORC2 consists of a...
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Translocation of Proteins into the Mitochondria01:19

Translocation of Proteins into the Mitochondria

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Mitochondrial precursors are translocated to the internal subcompartments via independent mechanisms involving distinct protein machineries called translocases.
Sorting of outer membrane proteins:
Mitochondrial outer membrane proteins are of two types: the transmembrane, beta-barrel porins, and the membrane-anchored, alpha-helical proteins. Beta-barrel porin precursors are translocated by the TOM complex and inserted into the outer mitochondrial membrane by the SAM complex. In contrast,...
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Related Experiment Video

Updated: Oct 29, 2025

Study of Protein-protein Interactions in Autophagy Research
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Bioinformatics Technologies in Autophagy Research.

Yu Xue1, Dong Wang2, Di Peng3

  • 1Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, Center for Artificial Intelligence Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China. xueyu@hust.edu.cn.

Advances in Experimental Medicine and Biology
|July 14, 2021
PubMed
Summary
This summary is machine-generated.

Bioinformatics tools enhance autophagy research by analyzing gene sequences and omics data. This review summarizes key computational methods and resources for understanding cellular regulation in autophagy.

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Area of Science:

  • * Bioinformatics
  • * Molecular Biology
  • * Cellular Biology

Background:

  • * Autophagy is a fundamental cellular process crucial for maintaining homeostasis.
  • * Bioinformatics offers powerful tools for deciphering complex regulatory mechanisms in autophagy.
  • * Advances in computational methods have significantly impacted autophagy research.

Purpose of the Study:

  • * To provide a comprehensive overview of bioinformatics technologies applied to autophagy research.
  • * To summarize recent progress in analyzing autophagy-related omics data.
  • * To highlight essential autophagy-related data resources for researchers.

Main Methods:

  • * Sequence analysis of autophagy genes, including homology identification, ortholog/paralog analysis, and evolutionary studies.
  • * Computational identification of autophagy-related sequence motifs using regular expressions, PSSM, and GPS.
  • * Analysis of omics data (transcriptomics, epigenomics, proteomics, etc.) using enrichment and network analysis.

Main Results:

  • * Bioinformatics tools facilitate the identification and evolutionary analysis of autophagy genes.
  • * Various computational methods are effective for analyzing diverse autophagy-related omics datasets.
  • * Several key autophagy gene and RNA databases are available for research support.

Conclusions:

  • * Bioinformatics plays an increasingly vital role in advancing autophagy research.
  • * Continued development of bioinformatics technologies will further enhance our understanding of autophagy.
  • * Integrated analysis of sequence and omics data using bioinformatics is essential for future discoveries.