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Related Concept Videos

Decision Making01:20

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
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Decision Making: Traditional Method01:14

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Experimental Approaches to Tissue Engineering
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Engineering Approaches to Study Cellular Decision Making.

Pamela K Kreeger1,2,3,4, Laura E Strong1, Kristyn S Masters1,4,5

  • 1Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA; email: kreeger@wisc.edu , kmasters@wisc.edu.

Annual Review of Biomedical Engineering
|January 13, 2018
PubMed
Summary
This summary is machine-generated.

Engineering approaches, including biomaterials and computational modeling, help unravel how cells make decisions based on complex environmental cues. This research explores how cells interpret and respond to various signals for better understanding of cellular behaviors.

Keywords:
cell–cell communicationextracellular matrixgrowth factorsintracellular signalingmicrofluidics

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Area of Science:

  • Biomedical Engineering
  • Cell Biology
  • Systems Biology

Background:

  • Cells exist in a complex environment with biochemical and biophysical cues.
  • These cues regulate critical cellular behaviors like adhesion, proliferation, migration, apoptosis, and differentiation.
  • Cellular decision-making integrates these cues, sensitive to individual cue type and combinations.

Purpose of the Study:

  • To review engineering-based approaches for studying cellular decision-making.
  • To highlight advancements in biomaterial platforms for controlled cue delivery.
  • To discuss computational modeling for analyzing cellular decision networks.

Main Methods:

  • Development of biomaterial platforms for precise control over biochemical and biophysical cues.
  • Controlled and tailored delivery of individual and combined extracellular cues.
  • Application of computational modeling to analyze complex cellular decision-making networks.

Main Results:

  • Engineering strategies offer powerful tools to dissect cellular responses to environmental stimuli.
  • Biomaterial platforms allow for systematic investigation of cue interactions.
  • Computational models provide insights into the intricate logic of cellular decision-making.

Conclusions:

  • Engineering-based approaches are crucial for understanding cellular decision-making processes.
  • Controlled cue delivery and computational analysis advance cell biology research.
  • This interdisciplinary approach enhances our comprehension of cellular behavior regulation.