Informational Biology
Life as Code, Signal, and Meaning
Author: (Draft)
Preface
Informational biology is the study of life through the lens of information: how it is encoded, transmitted, transformed, constrained, and interpreted across scales—from molecules to minds, from cells to ecosystems. This book proposes that biology is not merely chemistry in motion, but computation in context: matter organized by information under evolutionary pressure.
The aim is integrative rather than reductionist. We will draw from molecular biology, information theory, physics, computer science, and philosophy to build a coherent picture of living systems as informational processes embedded in physical substrates.
Part I — Foundations
Chapter 1: What Is Information?
Information is a relationship, not a substance. In its most general sense, information is a reduction of uncertainty relative to a system of possible states.
Shannon information quantifies uncertainty reduction in messages.
Algorithmic information measures the compressibility of descriptions.
Semantic information concerns meaning and function for a system.
Biology requires all three. DNA has Shannon information, genomes have algorithmic structure, and phenotypes embody semantic information because they do something in the world.
Chapter 2: The Physicality of Information
Information is physically instantiated. Landauer’s principle establishes that erasing information has an energetic cost. Living systems are thermodynamic machines that maintain low entropy internally by exporting entropy to their environment.
Life persists by:
Maintaining informational order
Coupling energy flow to constraint maintenance
Preventing informational decay faster than it accumulates
Chapter 3: Constraints and Causation
Biological causation is largely constraint-based rather than force-based. Information constrains possible system trajectories.
Examples:
Enzyme specificity constrains chemical reactions
Genetic regulatory networks constrain gene expression
Developmental pathways constrain morphology
Information acts by excluding alternatives.
Part II — Molecular Information
Chapter 4: DNA as a Digital Medium
DNA is a quaternary, discrete, error-correctable storage system.
Key properties:
Linear encoding
Redundancy
Modularity
Copying with variation
DNA does not contain a blueprint of the organism; it encodes a set of constraints that guide self-organization.
Chapter 5: The Genetic Code
The genetic code maps codons to amino acids. It is:
Nearly universal
Error-minimizing
Historically contingent
This code is an informational interface between nucleic acids and proteins—a translation system, not a simple chemical inevitability.
Chapter 6: Epigenetic Information
Not all biological information is sequence-based.
Epigenetic channels include:
DNA methylation
Histone modification
Chromatin architecture
Cellular inheritance of structure
Epigenetic information is context-dependent, reversible, and often responsive to environment.
Part III — Cellular Computation
Chapter 7: Cells as Information-Processing Systems
Cells sense, integrate, decide, and act.
Cellular information processing includes:
Signal detection
Amplification
Feedback
Memory
Signaling pathways function like noisy communication channels with redundancy and error correction.
Chapter 8: Gene Regulatory Networks
Gene expression is governed by networks, not linear chains.
Properties:
Nonlinearity
Attractors
Robustness
Plasticity
Cell types can be understood as stable informational states in high-dimensional regulatory landscapes.
Chapter 9: Development as Information Flow
Development is the progressive restriction of cellular possibilities.
Early embryos have high informational potential
Differentiation reduces entropy
Morphogenesis emerges from local rules
The genome sets boundary conditions; physics and interaction fill in the details.
Part IV — Evolutionary Information
Chapter 10: Evolution as Information Accumulation
Evolution accumulates information about environments.
Natural selection:
Filters random variation
Retains functional information
Embeds environmental regularities into genomes
This information is not foresight-driven, but historically contingent.
Chapter 11: Mutation, Noise, and Creativity
Noise is not merely destructive. It is a source of novelty.
Mutation introduces informational variation
Recombination reshuffles modules
Neutral drift explores state space
Evolution balances stability with exploration.
Chapter 12: Major Transitions in Informational Architecture
Major evolutionary transitions involve new ways of storing and transmitting information:
Genes → genomes
Cells → multicellular organisms
Individuals → societies
Nervous systems → symbolic language
Each transition increases informational bandwidth and coordination.
Part V — Organisms, Minds, and Meaning
Chapter 13: Nervous Systems and Predictive Information
Brains are prediction engines.
Sensory input updates internal models
Action minimizes prediction error
Memory compresses experience
Cognition is embodied, situated information processing.
Chapter 14: Meaning and Function
Meaning arises when information is used to maintain viability.
A signal has meaning if:
It is interpreted by a system
It guides action
It affects survival or reproduction
Biological semantics is grounded, not abstract.
Chapter 15: Consciousness as Integrated Information
While controversial, consciousness may reflect:
High integration
Differentiated informational states
Global availability of signals
This remains an open research frontier.
Part VI — Ecosystems and Beyond
Chapter 16: Ecological Information
Ecosystems exchange information via:
Chemical signals
Behavioral cues
Population dynamics
Niches encode information about organism–environment fit.
Chapter 17: Cultural and Symbolic Biology
Humans extend biology through external information storage:
Language
Writing
Technology
Culture evolves faster than genes but remains biologically grounded.
Chapter 18: Artificial Life and Synthetic Biology
Synthetic systems test our understanding of biological information.
Key questions:
What minimal information is required for life?
Can meaning emerge in artificial systems?
Where does biology end and technology begin?
Conclusion: Life as Informed Matter
Life is matter organized by information under constraint and selection. Informational biology does not replace chemistry or physics—it explains how they are harnessed to create persistence, adaptation, and meaning.
Understanding life informationally reshapes how we think about evolution, disease, intelligence, and our place in the universe.
Glossary (Selected)
Information: Reduction of uncertainty relative to a system
Constraint: A limitation on possible system states
Semantic information: Information with function for a system
Attractor: A stable state of a dynamical system
Epilogue
Biology is not written in ink or code alone. It is written in constraints, histories, and interpretations—an ongoing computation called life.
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