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Related Concept Videos

Multi-pass Transmembrane Proteins and β-barrels01:09

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In multi-pass transmembrane proteins, the polypeptide chain crosses the membrane more than once. The transmembrane polypeptide chain either forms an α-helix or β-strand structure. α-Helix containing multi-pass transmembrane proteins are ubiquitous, whereas β-strand containing ones are mainly found in gram-negative bacteria, mitochondria, and chloroplasts.
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The rough ER membrane synthesizes, assembles, and embeds transmembrane proteins in diverse topologies. These proteins function as transporters or channels and can remain in the ER membrane or are sent to the Golgi complex, lysosome, and cell membrane.
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A key characteristic of life is the ability to separate the external environment from the internal space. To do this, cells have evolved semi-permeable membranes that regulate the passage of biological molecules. Additionally, the cell membrane defines a cell’s shape and interactions with the external environment. Eukaryotic cell membranes also serve to compartmentalize the internal space into organelles, including the endomembrane structures of the nucleus, endoplasmic reticulum and...
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In contrast to passive transport, active transport involves a substance being moved through membranes in a direction against its concentration or electrochemical gradient. There are two types of active transport: primary active transport and secondary active transport. Primary active transport utilizes chemical energy from ATP to drive protein pumps embedded in the cell membrane. With energy from ATP, the pumps transport ions against their electrochemical gradients—a direction they would...
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Integral membrane proteins are proteins adhered to the lipid bilayer of a cell organelle or membrane. They can be of two types: transmembrane integral proteins that span the lipid bilayer and monotopic proteins that are attached to either side of the membrane but do not pass through it.
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Scientists identified the plasma membrane in the 1890s and its principal chemical components (lipids and proteins) by 1915. The model for plasma membrane structure, proposed in 1935 by Hugh Davson and James Danielli, was the first model to be widely accepted in the scientific community. The model was based on the plasma membrane's "railroad track" appearance in early electron micrographs. Davson and Danielli theorized that the plasma membrane's structure resembled a sandwich...
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Multimer-PAGE: A Method for Capturing and Resolving Protein Complexes in Biological Samples
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Multi-membrane search algorithm.

Qi Song1, Yourui Huang1,2, Wenhao Lai1

  • 1School of Electrical and Information Engineering, Anhui University of Science and Technology, Huainan, China.

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|December 6, 2021
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Summary
This summary is machine-generated.

A new multi-membrane search algorithm (MSA), inspired by cell biology, demonstrates competitive performance on unimodal and multimodal functions. MSA significantly outperforms existing algorithms on composite functions and engineering design problems.

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Area of Science:

  • Computational intelligence
  • Optimization algorithms
  • Bio-inspired computing

Background:

  • Optimization algorithms are crucial for solving complex problems.
  • Existing algorithms like MVO, GWO, MFO, and ALO have limitations in certain scenarios.
  • Cellular biological behaviors offer novel inspiration for algorithm design.

Purpose of the Study:

  • To introduce a novel multi-membrane search algorithm (MSA).
  • To evaluate MSA's performance against established algorithms using benchmark functions.
  • To assess MSA's applicability to real-world engineering design problems.

Main Methods:

  • Developing the multi-membrane search algorithm (MSA) based on cell secretion, division, and fusion.
  • Utilizing 19 benchmark functions for performance evaluation.
  • Comparing MSA with MVO, GWO, MFO, and ALO using consistent parameters (100 iterations, 10 population size, 50 repetitions).
  • Applying MSA to welded beam and pressure vessel design problems.

Main Results:

  • MSA shows competitive results on unimodal and multimodal benchmark functions.
  • MSA significantly outperforms MVO, MFO, ALO, and GWO on composite benchmark functions.
  • MSA achieves optimal solutions for welded beam design (1.7252) and pressure vessel design (5887.7052).

Conclusions:

  • MSA is a high-performance optimization algorithm.
  • MSA demonstrates superior performance on composite functions compared to MVO, MFO, ALO, and GWO.
  • MSA is effective for solving complex engineering design optimization problems.