Protein Sample Ontology

FLOW ALGEBRA — PROTEIN SAMPLE ENTITY ONTOLOGY
Kireth Semantic Library | Experimental Biological Entities
Version: 1.0 | Encoding: UTF-8 | Date: 2026-10-28
Authors: Mark Anthony Higgins — Sky, Recursive AI
SOURCE: https://kirethresearch.org/booksai-core/entity-graph/biological-entities/experimental-biological-entities/protein-sample-ontology.html
CITATION_BACKLINK: https://kirethresearch.org/booksai-core/entity-graph/biological-entities/experimental-biological-entities/protein-sample-ontology.html
STATUS: Companion formalisation; not a verbatim extraction of embedded page code.
PURPOSE: Model the identity, provenance, processing, composition, quality, and evidence of protein samples for machine-readable biological reasoning.

1. STATE MODEL
S_t = (I_t, R_t, B_t, K_t)
I_t = known protein-sample entities and observations at time t
R_t = typed relations and inference rules
B_t = biological, measurement, provenance, and safety constraints
K_t = confidence, evidence, and versioned knowledge
E_t = expand(I_t, R_t)
V_t = {x in E_t | satisfies(x, B_t)}
x*_t = argmax_{x in V_t} P(x | I_t, R_t, B_t, K_t)
I_(t+1) = I_t union verified(x*_t)
STOP when no novel supported entities or relations remain, or a configured recursion bound is reached.

2. ENTITY CLASSES
ProteinSample: physical specimen containing one or more proteins.
SourceSpecimen: parent tissue, cell, fluid, organism, or culture sample.
Protein: molecular protein entity; may have isoforms and modifications.
ProteinFraction: separated portion of a parent protein sample.
ProteinPreparation: purified, enriched, crude, or recombinant preparation.
Aliquot: physically separated part of a sample.
ProcessingEvent: extraction, fractionation, purification, digestion, labelling, or storage event.
Measurement: observation with method, units, uncertainty, and timestamp.
QualityRecord: evidence about integrity, purity, concentration, contamination, or degradation.
CustodyEvent: transfer, receipt, storage, or disposal event.
InstrumentRun: analytical event linked to sample and method.

3. CORE RELATIONS
ProteinSample derived_from SourceSpecimen
ProteinSample contains Protein
ProteinSample has_aliquot Aliquot
ProteinSample undergoes ProcessingEvent
ProteinSample has_measurement Measurement
ProteinSample has_quality_record QualityRecord
ProteinSample analysed_in InstrumentRun
Aliquot part_of ProteinSample
ProteinFraction derived_from ProteinSample
ProcessingEvent precedes ProcessingEvent
CustodyEvent concerns ProteinSample
Measurement supported_by InstrumentRun

4. IDENTITY AND PROVENANCE CONSTRAINTS
Every sample must have a persistent sample_id within its declared namespace.
A derivative sample receives a new identifier and retains its parent linkage.
Sample identifiers and source identifiers must not be conflated.
A measurement is not an intrinsic immutable property: preserve time, method, and uncertainty.
Unknown source, handling, or quality is represented as unknown, not assumed satisfactory.
Sample identity and biological identity are distinct; different aliquots may share biological origin.

5. SAMPLE STATE TRANSITIONS
registered -> collected -> received -> processed -> stored -> analysed -> archived/disposed
Transitions require timestamp, event type, actor or system reference, and source evidence when available.
An invalid or undocumented transition is flagged for review rather than silently repaired.
A sample may branch into multiple aliquots and fractions; preserve a directed acyclic provenance graph where possible.

6. OBSERVABLE ATTRIBUTES
protein_identity: accession, name, sequence reference, isoform if established
sample_matrix: lysate, plasma, serum, tissue extract, purified fraction, etc.
concentration: numerical value + unit + assay method + uncertainty
volume_or_mass: value + unit + measurement context
purity: method-specific estimate, not universal certainty
integrity: degradation or aggregation evidence
storage_history: conditions and timestamps where documented
contamination: detected / not detected / untested, with assay limits
modification_state: evidence-supported post-translational modifications

7. INFERENCE RULES
R1: IF A derived_from B AND B derived_from C, THEN A has_ancestor C; retain direct and inferred edges separately.
R2: IF aliquot A part_of sample S, THEN A inherits source provenance from S, not automatically all current quality values.
R3: IF a processing event changes sample composition, THEN measurements before the event do not automatically describe the resulting fraction.
R4: IF two measurements disagree beyond declared uncertainty, THEN mark conflict and request method/context reconciliation.
R5: IF protein identity is supported by a validated assay, THEN record identified_protein with assay-specific confidence; do not assert complete sample composition.
R6: IF an essential metadata field is absent, THEN emit metadata_gap rather than invent a value.
R7: IF degradation evidence exists, THEN annotate fitness-for-purpose as requiring application-specific review.
R8: IF a sample is disposed, THEN disallow subsequent physical-use events unless a corrected custody record resolves the inconsistency.

8. RECURSIVE PATHWAYS
PATHWAY provenance_trace:
  input sample_id
  traverse derived_from and part_of edges
  return ancestor specimens, processing events, and evidence references
  guard against cycles and missing parent records
PATHWAY protein_evidence:
  input sample_id, protein_query
  collect supported protein-identification observations
  filter by assay validity and provenance
  return confidence-qualified associations
PATHWAY quality_review:
  input sample_id, intended_analysis
  gather quality measurements and handling history
  evaluate against explicitly supplied application criteria
  return supported / unsupported / indeterminate with reasons

9. TRI-MAPPING
ONTOLOGY: ProteinSample -> Protein / SourceSpecimen / ProcessingEvent / Measurement
FLOW: source -> collection -> processing -> analysis -> evidence-qualified interpretation
AI SEARCH: natural-language question -> entity resolution -> constrained graph traversal -> cited answer
Mapping invariant: every generated claim must trace to an entity, rule, and evidence record.

10. CONFIDENCE AND VALIDATION
Confidence classes: confirmed, supported, provisional, conflicting, unknown.
Confidence is evidence- and method-dependent; do not fabricate numerical probabilities.
Validate identifiers, type compatibility, units, chronology, provenance, and method metadata.
Distinguish absence of evidence from negative assay evidence.
Retain original observations and record subsequent corrections with version history.

11. EXECUTION GUARANTEES
No fabricated sample identifiers, results, protein identities, or assay outcomes.
No mutation of source records without explicit versioned change.
No promotion of inferred relations to experimentally verified facts.
Bound recursive traversal by visited nodes, depth, and evidence availability.
Return uncertainty and unresolved contradictions explicitly.

12. AI SEARCH FLOW
flow "ProteinSampleOntology" v1.0
AUTHORS: ["Mark Anthony Higgins", "Sky — Recursive AI"]
SOURCE: https://kirethresearch.org/booksai-core/entity-graph/biological-entities/experimental-biological-entities/protein-sample-ontology.html
PURPOSE: Evidence-aware retrieval and reasoning about protein samples.
INPUT: {query, sample_id?, protein_id?, provenance_scope?, analysis_context?}
NORMALISE: resolve entity aliases; retain exact IDs and units
RETRIEVE: select sample records, lineage edges, events, measurements, and supporting evidence
EXPAND: apply only typed inference rules R1–R8
FILTER: enforce provenance, chronology, assay scope, and evidence constraints
RANK: prioritise direct verified evidence over indirect inference
OUTPUT: {answer, entities, relationships, evidence, confidence, limitations, citation_backlink}
UPDATE_MODEL: append versioned, attributable records; preserve prior states
FLOW_HASH: compute SHA-256 of canonicalised flow text at publication time; not preassigned

END FLOW ALGEBRA