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Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
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What is information?†.

Christoph Adami1

  • 1Department of Microbiology and Molecular Genetics, Department of Physics and Astronomy, BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824, USA adami@msu.edu.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|February 10, 2016
PubMed
Summary
This summary is machine-generated.

This study clarifies the mathematical concepts of information and entropy, highlighting their distinct yet related nature. Understanding information through prediction is crucial for fields like physics and biology.

Keywords:
Bayesian inferenceentropyinformation

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Area of Science:

  • Information theory
  • Mathematical physics
  • Theoretical biology

Background:

  • The precise mathematical definition of information is distinct from its relationship with knowledge.
  • The concepts of entropy and information are deeply related but often confused in scientific literature.
  • A clear distinction between entropy and information is necessary for rigorous scientific discourse.

Purpose of the Study:

  • To provide an elementary introduction to the concepts of entropy and information.
  • To rigorously define entropy and information while explaining them intuitively.
  • To argue for the importance of understanding information in terms of prediction across multiple scientific disciplines.

Main Methods:

  • Conceptual clarification of information theory principles.
  • Rigorous mathematical definitions of entropy and information.
  • Intuitive explanations of complex concepts for broader accessibility.

Main Results:

  • Information can be precisely defined mathematically.
  • Entropy and information are distinct concepts requiring careful application.
  • A predictive framework for information is essential for various scientific fields.

Conclusions:

  • A clear understanding of information, defined through prediction, is vital for advancements in physics and biology.
  • Distinguishing between entropy and information enhances clarity in scientific communication.
  • This work provides a foundational understanding for applying information theory in diverse scientific contexts.