Biological Information : : New Perspectives - Proceedings Of The Symposium.

Biological Information : : New Perspectives - Proceedings Of The Symposium.

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Bibliographic Details
:
Sanford, John C.
TeilnehmendeR:
Marks Ii, Robert J.
Behe, Michael J.
Dembski, William A.
Gordon, Bruce L.
Place / Publishing House:Singapore : : World Scientific Publishing Company,, 2013.
©2013.
Year of Publication:2013
Edition:1st ed.
Language:English
Online Access:
Physical Description:1 online resource (584 pages)
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Table of Contents:
  • Intro
  • Contents
  • Title Page
  • Acknowledgements
  • General Introduction
  • References and Notes
  • Section One Information Theory &amp
  • Biology: Introductory Comments Robert J. Marks II
  • 1.1.1 Biological Information - What is It? Werner Gitt, Robert Compton and Jorge Fernandez
  • Introduction
  • Defining Subsets of Information
  • Distinguishing Attributes of Information
  • Code plus syntax
  • Meaning
  • Expected Action
  • Intended Purpose
  • The Definition of Universal Information
  • The Nature of Universal Information
  • Does Biological Life Contain Universal Information?
  • Code plus Syntax
  • Abstract Meaning
  • The Expected Acti on
  • The Intended Purpose
  • UI Senders, Transmitters and Receivers
  • The Existence, Validity and Significance of Universal Information
  • Conclusion
  • References
  • 1.1.2 A General Theory of Information Cost Incurred by Successful Search William A. Dembski, Winston Ewert and Robert J. Marks II
  • 1. The Search Matrix
  • Example 1.1: Uniform random sampling with perfect knowledge
  • Example 1.2: Uniform random sampling with zero knowledge
  • Example 1.3: Uniform random sampling with partial knowledge
  • Example 1.4: Smooth gradient fitness with single peak
  • 2. General Targeted Search
  • 3. Search Examples
  • Example 3.1: Uniform random sampling with perfect knowledge and without replacement
  • Example 3.2: Easter egg hunt
  • Example 3.3: Competitive search
  • Example 3.4: Tournament play
  • Example 3.5: Populati on search
  • 4. Information and Efficiency Measures
  • 5. Liftings and Lowerings
  • 6. Conservation of Information - The Uniform Case
  • 7. Conservation of Information - The General Case
  • 8. Regulating the Information Industry
  • Acknowledgment
  • References and Notes
  • 1.1.3 Pragmatic Information John W. Oller, Jr.
  • Introduction
  • Ranking in Sign Systems.
  • Tampering with the Sign Architecture
  • Pragmatic Mapping
  • The Vanishing Ratio of Meaningful to Random Strings
  • The Logical Sequence for Discovering Meaning
  • Conclusions
  • Addendum
  • Acknowledgments
  • References
  • 1.2.1 Limits of Chaos and Progress in Evolutionary Dynamics William F. Basener
  • 1. Introduction
  • 1.1 Goals and Perspective.
  • 1.2 History and Applicati on of Topology and Dynamical Systems
  • 1.3 General Questions in Evolutionary Models
  • 2. Evolutionary Models and Dynamical Systems
  • 2.1. Simple Populati on Models
  • 2.2. Simple Mutati on-Selection Models
  • 2.3. Population Models with Mutati on-Selection
  • 3. Chaos and Recurrent Behavior
  • 4. Conclusions
  • References
  • 1.2.2 Tierra: The Character of Adaptation Winston Ewert, William A. Dembski and Robert J. Marks II
  • 1. Introduction
  • 2. Description of Tierra
  • 2.1 Programs
  • 2.2 Ancestor
  • 2.3 Parallel Tierra
  • 2.4 Network Tierra
  • 3. Looking for complexity
  • 4. Examples
  • 4.1 Parasite
  • 4.2 Immunity
  • 4.3 Hyper-parasites
  • 4.4 Social behavior
  • 4.5 Cheater
  • 4.6 Shorter program
  • 4.7 Loop unrolling
  • 4.8 Parallel code
  • 4.9 Recap
  • 5. Summary
  • Acknowledgments
  • 6. Appendix: Tierra program comparisons
  • 6.1 Ancestor and parasite
  • 6.2 Immunity
  • 6.3 Ancestor and hyper-parasite
  • 6.4 Hyper-parasite and social program
  • 6.5 Social program and cheater
  • 6.6 Ancestor and short code
  • 6.7 Loop unrolling
  • 6.8 Parallel
  • References
  • 1.2.3 Multiple Overlapping Genetic Codes Profoundly Reduce the Probability of Beneficial Mutation George Montañez, Robert J. Marks II, Jorge Fernandez and John C. Sanford
  • 1. Introduction
  • 2. Method and Results
  • 2.1 The Model
  • 2.2 Analyses
  • 2.2.1 First Level of Analysis:
  • 2.2.2 Second Level of Analysis:
  • 2.2.3 Third Level of Analysis:
  • 2.2.4 Summary of Results:
  • 3. Discussion.
  • 3.1 Possible Objections
  • 4. Conclusions
  • References
  • 1.3.1 Entropy, Evolution and Open Systems Granville Sewell
  • 1. Compensation
  • 2. The Equations of Entropy Change
  • 3. A Tautology
  • 4. The Common Sense Law of Physics
  • 5. Conclusions
  • 6. References
  • 1.3.2 Information and Thermodynamics in Living Systems Andy C. McIntosh
  • 1. Introduction
  • 2. Biological information storage and retrieval - thermodynamic issues
  • 2.1 Thermodynamics and isolated systems
  • 2.2 Non isolated systems
  • 2.2.1 Entropy deficiency
  • 2.2.2 Open systems and machinery
  • 2.3 Can negative entropy be harvested from somewhere else?
  • 3. Free energy and Machines
  • 3.1 Free energy
  • 3.2 Machines and raised free energies
  • 3.3 Thermodynamic law of non-isolated systems
  • 3.4 Crystal formation
  • 3.5 Bio polymer formation
  • 4. A different paradigm: Thermodynamics constrained by functional information
  • 4.1 A different paradigm: Information definitions
  • 4.2 A different paradigm: principles of information and thermodynamics
  • 4.2.1 Principles of information exchange
  • 4.2.2 Principles of information interaction with energy and matter in biological systems
  • 5. Conclusions
  • Acknowledgement
  • References
  • Section Two Biological Information and Genetic Theory: Introductory Comments John C. Sanford
  • 2.1 Not Junk After All: Non-Protein-Coding DNA Carries Extensive Biological Information Jonathan Wells
  • 1. Introduction
  • 2. Widespread Transcription Into RNAs That Are Probably Functional
  • 3. Direct Evidence for Some Specific Functions of Non-Protein- Coding RNAs
  • 4. Functions of Non-Protein-Coding DNA That Are Not Determined by Precise Nucleotide Sequences
  • 4.1 The Length of DNA Sequences
  • 4.2 Chromatin Organization
  • 4.3 Chromosome Arrangement in the Nucleus
  • 5. Conclusion: Multiple Levels of Biological Information
  • Addendum.
  • Acknowledgments
  • References
  • 2.2 Can Purifying Natural Selection Preserve Biological Information? Paul Gibson, John R. Baumgardner, Wesley H. Brewer and John C. Sanford
  • Introduction
  • Results
  • Conditions allowing perfect purifying selection
  • Effects of high mutati on rate and mutation-mutation interference
  • Effects of environmental variance
  • Effects of varying degrees of randomness within the selecti on process
  • Effects of minimal levels of noise from multiple sources
  • Effects of larger population size, more time, and more recombination
  • Experiments using the latest estimate of human mutation rate and fitness effect distribution
  • Discussion
  • General Implications
  • Robustness of Findings
  • Potential Effects of Other Factors
  • Conclusion
  • Materials and Methods
  • Acknowledgments
  • References
  • Appendix 1: Key parameter settings and their basis
  • 2.3 Selection Threshold Severely Constrains Capture of Beneficial Mutations John C. Sanford, John R. Baumgardner and Wesley H. Brewer
  • Introduction
  • Results
  • Conditions allowing optimal selection for beneficial mutations
  • Effect of environmental variance
  • Introduction of probability into the selection process
  • Effect of high mutation rate and consequent selecti on interference among beneficial mutations
  • Effect of extremely beneficial mutations
  • Effect of adding deleterious mutations
  • Effect of multiple sources of noise, at minimal levels
  • Modest levels of noise with a larger population
  • The effect of time on STd and STb values
  • Discussion
  • Can low-impact beneficial mutations contribute to genome building?
  • Can high-impact beneficial mutations explain the origin of the genome?
  • Can equal-but-opposite compensating mutations stop degeneration?
  • Can high-impact compensating beneficial mutations stop degeneration?.
  • Might beneficial mutations be common?
  • Possible criticisms
  • Concluding comments
  • Methods
  • Addendum -
  • Acknowledgments
  • References
  • Appendix I: Key parameter settings and their justification:
  • 2.4 Using Numerical Simulation to Test the "Mutation-Count" Hypothesis Wesley H. Brewer, John R. Baumgardner and John C. Sanford
  • Introduction
  • Methods
  • Results
  • Discussion
  • Acknowledgements
  • References
  • 2.5 Can Synergistic Epistasis Halt Mutation Accumulation? Results from Numerical Simulation John R. Baumgardner, Wesley H. Brewer and John C. Sanford
  • Introduction
  • Methods
  • Modeling general epistasis
  • Modeling additive interactions
  • Modeling multi plicative interactions
  • Modeling synergistic epistasis
  • Results
  • Preliminaries
  • Large SE effects and modest selection pressure
  • Extreme SE effects and moderate selection pressure
  • Extremely exaggerated SE effects and extreme selection pressure
  • Discussion
  • The importance of genic interactions
  • The significance of SE
  • Testing the limits of SE
  • Modeling SE realistically
  • Pros and cons of the SE hypothesis
  • Conclusions
  • References
  • 2.6 Computational Evolution Experiments Reveal a Net Loss of Genetic Information Despite Selection Chase W. Nelson and John C. Sanford
  • Introduction
  • Mendel's Accountant
  • Avida
  • Selection threshold and genetic entropy
  • Methods
  • Experiments using Mendel's Accountant
  • Experiments using Avida
  • Results
  • Experiments using Mendel's Accountant
  • Experiments using Avida
  • Discussion
  • Selection threshold and genetic entropy
  • High-impact beneficial mutations
  • Distribution of mutational fitness effects
  • Junk DNA
  • Irreducible complexity and the waiting time to beneficial mutation
  • Reductive evolution
  • Conclusions
  • Addendum
  • Acknowledgments
  • References.
  • 2.7 Information Loss: Potential for Accelerating Natural Genetic Attenuation of RNA Viruses Wesley H. Brewer, Franzine D. Smith and John C. Sanford.

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