TL;DR
Why don’t living things fall apart like everything else in the universe? They’re information-processing machines that use energy to build and maintain order. DNA isn’t just a molecule: it is functional code shaped by billions of years of evolutionary debugging. Every major leap in life’s complexity (cells, multicellularity, brains) happened when organisms found new ways to store and use information. This isn’t metaphor. Diseases are information glitches. Development is orchestrated data flow. Evolution is an algorithm discovering useful sequences from impossibly vast possibilities. Understanding biology without information is like understanding software by only studying transistors. You need both the hardware and the code.
The Full Story
Information as Biology’s Organizing Principle
The concept of information represents one of the most profound intellectual shifts in modern biology - not merely a metaphor, but a fundamental organizing principle that reveals why living systems behave so differently from simple physical systems.
Why Every Biologist Should Care
Consider this paradox: thermodynamics tells us that entropy always increases, yet living organisms create and maintain extraordinary order. They grow, reproduce, and evolve increasingly complex structures. This apparent contradiction dissolves when we recognize that biological systems are fundamentally information-processing entities that use energy to create, maintain, and transmit information against the gradient of entropy.
Without understanding information, you’re missing the forest for the trees. You might catalog every molecular interaction in a cell, yet fail to grasp why those particular interactions exist and persist across billions of years of evolution.
What Is Biological Information?
Biological information is specification with functional consequences. This definition has three critical components:
Specification: The DNA sequence ATGCCG specifies something different from ATGCCT. The difference matters because it changes which amino acid gets incorporated into a protein.
Function: Not all specification is information. Random sequences specify states, but biological information specifically refers to sequences that do work - they fold proteins, regulate genes, or guide development. Information is that which reduces uncertainty about functionally relevant outcomes.
Context-dependence: Here’s where it gets philosophically rich: information only exists in relation to an interpretive system. The genetic code is meaningless without ribosomes, tRNAs, and the entire translation machinery. This makes biological information fundamentally different from Shannon information (which treats all sequences as equivalent) and closer to semantic information.
The Philosophical Foundation
John Maynard Smith and Eors Szathmáry’s concept of major evolutionary transitions provides the clearest argument for information’s centrality. Every major leap in biological complexity - from replicating molecules to chromosomes, from prokaryotes to eukaryotes, from single cells to multicellular organisms - involved new ways of storing, transmitting, or processing information.
This isn’t coincidental. It reflects a deep principle: evolution is an information-generating process. Natural selection acts as an algorithm that discovers functional sequences from the incomprehensibly vast space of possible sequences. The human genome contains roughly 3 billion base pairs, representing one arrangement from 4(3×109) possibilities - a number so large it makes the number of atoms in the universe look quaint.
The Teleosemantics Argument
Here’s where philosophy of science becomes indispensable. How can we talk about biological information carrying “meaning” without invoking vitalism or teleology?
The answer lies in teleosemantics (primarily developed by Ruth Millikan and Karen Neander): biological information has meaning because of its evolutionary history. A gene “means” build a particular protein because organisms with that sequence-to-function relationship survived and reproduced more successfully than those without it. The meaning is grounded in causal history, not mysterious purpose.
This resolves the apparent circularity: genes specify proteins, but only because evolution selected genes that specify useful proteins. Information and function co-evolve.
Information Flow as Causation
Ernst Mayr distinguished between proximate and ultimate causation in biology. Information provides the bridge:
Proximate: How does development work? Through precisely orchestrated information flows - transcription factors binding enhancers, signaling cascades, epigenetic marks guiding cell fate.
Ultimate: Why do these particular information flows exist? Because they encoded solutions to evolutionary problems.
Every developmental process, every physiological response, every behavior involves information transfer that was selected for its functional consequences. When you study any biological phenomenon without considering its information architecture, you’re like someone trying to understand software by examining only the physics of transistors.
The Counterargument Worth Considering
Some philosophers (notably C. Kenneth Waters) argue that “genetic information” is a misleading metaphor that obscures the distributed, context-dependent nature of causation in development. They’re right that we shouldn’t be genocentric - information exists at multiple levels (epigenetic, cellular, ecological).
But this critique actually strengthens the case for informational thinking: it forces us to recognize that biology involves information processing at every scale, from molecular to ecological. The question isn’t whether information is relevant, but rather which information flows matter for explaining a given phenomenon.
Practical Implications
Understanding information transforms how you think about:
- Disease: Many pathologies are information-processing failures (misfolded proteins, regulatory mutations, disrupted signaling)
- Evolution: Not just selection on phenotypes, but on the information that generates phenotypes
- Synthetic biology: Engineering organisms means engineering information-processing systems
- Drug development: Intervening in specific information flows rather than bluntly blocking pathways
In your clinical research work, every endpoint you measure ultimately traces back to information flows that went right or wrong. Survival analysis isn’t just about time-to-event - it’s about how long information-processing systems (patients’ bodies) can maintain function against entropic decay and pathological perturbation.
The Bottom Line
Thinking informationally doesn’t replace molecular, cellular, or organismal biology - it integrates them. It reveals the logic underlying the mechanisms. And that logical structure is what makes biology more than physics, what makes it a science of functional organization maintained across time through information transmission.
The BioLogical Footnote
To ignore information in biology is to study the hardware while ignoring the software. Both are real, both are causal, both are necessary for explanation.
To Explore Further
Biological Information | Stanford Encyclopedia of Philosophy