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Related Concept Videos

Migration00:53

Migration

Migration is long-range, seasonal movement from one region or habitat to another. This common strategy, carried out by many different organisms around the world, is an adaptive response that typically corresponds to changes in an organism’s environment, like resource availability or climate. Migrations can involve huge groups of thousands of animals as well as single individuals traveling alone and can range from thousands of kilometers to just a few hundred meters.
Types of Genetic Transfer Between Organisms02:18

Types of Genetic Transfer Between Organisms

Genetic transfer occurs when genetic information is passed from one organism to another. It occurs via two mechanisms: vertical gene transfer and horizontal gene transfer. Vertical gene transfer occurs when genetic information is transferred from one generation to the next, which happens much more frequently than horizontal gene transfer. Both sexual and asexual reproduction are forms of vertical gene transfer, where one or more organisms pass some or all of their genome onto their progeny.
ER Retrieval Pathway01:45

ER Retrieval Pathway

In the secretory pathway, vesicles transport proteins from one cellular compartment to another in forward transport to deliver the protein to its correct location. Occasionally, misfolded proteins and incorrect proteins escape their original compartments, and a retrieval pathway is used to return the escaped proteins to their original compartment.
The ER uses many checkpoints to prevent the entry of incorrectly folded or a resident protein as cargo onto a transport vesicle. These mechanisms...

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Related Experiment Video

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A Simple Migration/Invasion Workflow Using an Automated Live-cell Imager
09:17

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Published on: February 2, 2019

Remote data retrieval for bioinformatics applications: an agent migration approach.

Lei Gao1, Hua Dai, Tong-Liang Zhang

  • 1College of Information Sciences and Technology, Donghua University, Shanghai, China. dr.leigao@gmail.com

Plos One
|June 25, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel agent migration approach for mobile environments to efficiently retrieve biological data. It overcomes limitations of current methods, enabling offline data access and reducing network strain.

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Area of Science:

  • Bioinformatics
  • Mobile Computing
  • Distributed Systems

Background:

  • Existing remote biological data retrieval methods often require continuous online connectivity, straining mobile device resources and network bandwidth.
  • Current approaches are not optimized for mobile environments, facing challenges with limited device capabilities, poor network quality, and intermittent user connectivity.

Purpose of the Study:

  • To develop a robust system for automatic remote biological data retrieval in mobile environments.
  • To address limitations of existing methods, including high latency, limited bandwidth, and unreliable network connections.
  • To propose a solution suitable for mobile computing constraints such as limited resources and intermittent online presence.

Main Methods:

  • Integration of an agent migration approach with a multi-agent system.
  • Developing a system architecture and migration strategy for agent mobility.
  • Implementing security authentication mechanisms for agent migration.
  • Demonstrating the approach using remote data retrieval from GenBank.

Main Results:

  • The proposed agent migration approach effectively overcomes high latency and limited bandwidth issues.
  • The system is well-suited for the constraints of mobile computing environments.
  • Demonstrated feasibility of retrieving remote biological data (GenBank) using the developed system.

Conclusions:

  • Agent migration within a multi-agent system offers a viable solution for efficient remote biological data retrieval in mobile settings.
  • The approach enhances accessibility and reliability of biological data access for mobile researchers.
  • The developed system architecture, migration strategy, and security measures provide a foundation for future mobile bioinformatics applications.