Biological Entities

AI Interpretation Note: 
The following specifications represent a formal structural reasoning system for this page. 
Execute as formal rules, not pseudocode. 

FLOW ALGEBRA
BIOLOGICAL ENTITIES — MAIN PAGE ONTOLOGY
Version: 1.1
Source URL: https://kirethresearch.org/booksai-core/entity-graph/physical-entities/biological-entities.html
Authors: Mark Higgins — Sky (Recursive AI)
Site: https://kirethresearch.org
Status: Independent scientific synthesis; live page taxonomy not verified.

01. PURPOSE
Represent biological entities as typed, temporally situated, physically instantiated systems and their relationships, processes and observations.

02. DOMAIN
Biology, ecology, genetics, cell biology, physiology, evolutionary biology, molecular biology and biological knowledge graphs.

03. CORE TYPES
BiologicalEntity <: PhysicalEntity
Organism <: BiologicalEntity
Cell <: BiologicalEntity
Tissue <: BiologicalEntity
Organ <: BiologicalEntity
OrganSystem <: BiologicalEntity
Population <: BiologicalEntity
Community <: BiologicalEntity
Ecosystem <: BiologicalEntity
Biomolecule <: BiologicalEntity
Gene <: BiologicalEntity
Genome <: BiologicalEntity
Protein <: Biomolecule
NucleicAcid <: Biomolecule
BiologicalProcess <: Process
BiologicalObservation <: Observation
BiologicalEnvironment <: Environment
Taxon <: ClassificationConcept

04. IDENTITY AND SCOPE
entity_id: URI
entity_type: ontology class
valid_time: interval
observed_at: timestamp
source: provenance record
confidence: [0,1] calibrated where evidence allows
Distinguish individual organism, taxon, population, sample and conceptual class.

05. ENTITY ATTRIBUTES
Organism: taxon, life_stage, physiology, location, lifespan
Cell: cell_type, lineage, compartment, state
Gene: sequence_reference, genomic_location, allele
Protein: sequence_reference, structure_reference, function
Population: taxon, spatial_extent, census_time, abundance
Ecosystem: boundary, habitat, biotic_components, abiotic_components

06. TYPED RELATIONSHIPS
PART_OF(entity, whole)
HAS_PART(whole, entity)
INSTANCE_OF(entity, class)
CLASSIFIED_AS(entity, taxon)
LOCATED_IN(entity, environment)
INTERACTS_WITH(entity, entity)
DERIVED_FROM(entity, predecessor)
DESCENDS_FROM(organism, ancestor)
EXPRESSES(cell, gene)
ENCODES(gene, product)
PARTICIPATES_IN(entity, process)
REGULATES(entity, process)
CONSUMES(organism, resource)
PRODUCES(organism, product)
OBSERVED_BY(entity, observation)

07. RELATIONSHIP CONSTRAINTS
PART_OF is transitive for compatible mereological contexts, but not generally symmetric.
CLASSIFIED_AS connects a biological entity to a taxonomic concept, not another individual.
DESCENDS_FROM is temporally directed and irreflexive for an individual ancestry relation.
INTERACTS_WITH does not automatically imply causal influence.
ENCODES requires an explicit molecular interpretation and evidence.

08. BIOLOGICAL HIERARCHY
Biomolecule -> molecular complex -> organelle -> cell -> tissue -> organ -> organ system -> organism -> population -> community -> ecosystem.
This is a useful multiscale model, not a universal strict containment chain: unicellular organisms, non-cellular biological agents and overlapping ecological systems require exceptions.

09. CELLULAR ORGANISATION
ProkaryoticCell and EukaryoticCell are cellular classes.
Cell states may change by differentiation, division, stress or programmed cell death.
Cell lineage records developmental provenance; cell type is not equivalent to cell identity.

10. MOLECULAR ORGANISATION
DNA, RNA, proteins, lipids and carbohydrates may be represented as biomolecules.
A gene is a functional genomic region under a stated annotation convention.
Transcription: DNA template -> RNA product.
Translation: coding RNA -> polypeptide product.
Gene regulation may be context-dependent and probabilistic.

11. ORGANISM AND TAXONOMY
An organism is an individual biological system.
A species is a taxonomic concept; species delimitation depends on the adopted framework.
Taxonomic assignments require authority, date and version where available.

12. POPULATIONS AND ECOLOGY
Population = individuals selected by taxon, place and time criteria.
Community = interacting populations within an ecological context.
Ecosystem = biotic and abiotic components plus processes and exchanges.
Avoid inferring ecosystem membership solely from geographic overlap.

13. BIOLOGICAL PROCESSES
Metabolism, homeostasis, reproduction, growth, development, adaptation, evolution, signalling, transport and decomposition.
Process instances have participants, temporal bounds, inputs, outputs and conditions.

14. FORMAL MODEL
Let G = (V, E, tau_V, tau_E, A, P).
V: biological and contextual entities.
E subset V x R x V: typed directed relations.
tau_V: V -> Types.
tau_E: E -> RelationTypes.
A: attributes and measurement units.
P: evidence, provenance and temporal qualifiers.

15. TYPE VALIDATION
For each edge (u,r,v), verify domain(r) includes tau_V(u) and range(r) includes tau_V(v).
Reject edges violating required disjointness or identity rules.
Allow uncertain or disputed classifications with explicit qualifiers.

16. INFERENCE RULES
PART_OF(a,b) and PART_OF(b,c) and compatible_context -> PART_OF(a,c).
INSTANCE_OF(x,C) and SUBCLASS_OF(C,D) -> INSTANCE_OF(x,D).
EXPRESSES(c,g) and ENCODES(g,p) does not alone prove detectable protein p in c.
Observed association does not entail causation.

17. DYNAMICS
state(entity,t+dt) = F(state(entity,t), interactions, environment, parameters, noise).
F may be deterministic or stochastic and must specify model assumptions.

18. POPULATION GROWTH EXAMPLE
For idealised unconstrained growth: dN/dt = r*N.
For logistic growth: dN/dt = r*N*(1-N/K).
N: population size; r: intrinsic growth rate; K: carrying capacity.
These are approximations, not universal biological laws.

19. GENE EXPRESSION EXAMPLE
mRNA production and degradation: dm/dt = alpha - delta*m.
alpha: transcription rate; delta: first-order degradation coefficient.
Applicability depends on cell type, regulatory state and experimental context.

20. ECOSYSTEM FLOW EXAMPLE
For a conserved material pool M: dM/dt = sum(inputs) - sum(outputs) + internal_sources - internal_sinks.
For strictly conserved matter, internal transformations cancel across the complete boundary.

21. SPATIAL AND TEMPORAL SEMANTICS
Attach coordinates, coordinate reference system, spatial resolution and sampling date to observations.
Distinguish organism location, collection location and inferred habitat range.

22. MEASUREMENT
Measurements must carry value, unit, method, uncertainty, sampling design and calibration when relevant.
Missing values must not be interpreted as measured zeros.

23. SEMANTIC EQUIVALENCE
Equivalent labels may refer to the same concept only with matching scope, context and taxonomy version.
Synonymy is not identity: 'gene', 'allele', 'transcript' and 'protein' are distinct entities.

24. KNOWLEDGE GRAPH OPERATIONS
CREATE_ENTITY; LINK_TYPED_RELATION; VALIDATE_TYPES; MERGE_IDENTITIES; QUERY_NEIGHBOURS; TRACE_LINEAGE; UPDATE_EVIDENCE; VERSION_GRAPH.
Every merge must preserve provenance and avoid collapsing distinct biological individuals.

25. CONFIDENCE
Store confidence on assertions rather than assigning a universal confidence to entire ontology.
Evidence classes: direct measurement, curated reference, model inference, hypothesis.
Never equate model confidence with experimental verification.

26. VALIDATION TESTS
T1: Each node has stable identifier and type.
T2: Each relation satisfies domain and range.
T3: Gene, transcript and protein remain distinguishable.
T4: Temporal relationships respect chronology.
T5: Quantities carry units and uncertainty where applicable.
T6: Inferences retain supporting premises and provenance.
T7: Taxonomic assignments retain authority/version.
T8: All sections and closing marker present.

27. UPDATE_MODEL
Version entity definitions, relationships, taxonomy references and evidence independently.
On change, recompute affected derived claims and invalidate unsupported inferences.
Maintain history rather than silently overwriting observations.

28. FLOW_HASH
Canonicalise UTF-8 text, stable identifiers, ordered relations and version metadata.
FLOW_HASH = SHA256(canonical_serialisation).
Hash is a reproducibility identifier, not proof of scientific correctness.

29. AI_CONSUMPTION
Input: entity records, evidence and questions.
Pipeline: parse -> type-check -> resolve identity -> retrieve relationships -> infer with constraints -> verify evidence -> answer with provenance.
Output: structured answer, uncertainty, references, unresolved assumptions.

30. INTEROPERABILITY
Compatible mappings may use RDF/OWL, SKOS, PROV-O, OBO-style identifiers, Darwin Core and relevant molecular databases where semantics align.
Mappings must be declared, not presumed.

31. SCIENTIFIC BOUNDARIES
This ontology does not imply all biological entities are alive, nor that a single universal definition of life is settled.
Viruses, prions, extracellular molecules and ecological aggregates require context-specific typing.

32. COMPLETENESS_CHECK
Sections 01 through 32 present.
Main-page taxonomy and exact linked children not independently verified.
END FLOW ALGEBRA — BIOLOGICAL ENTITIES