Biological Measurements

# Biological Measurements Ontology — Flow Algebra

URL: https://kirethresearch.org/booksai-core/ontologies/mathematical-ontologies/measurement-units-ontologies/biological-measurements.html

FLOW BiologicalMeasurementsOntology {

  DOMAIN:
    Mathematical Ontologies
    -> Measurement & Units Ontologies
    -> Biological Measurements Ontology

  PURPOSE:
    Represent biological measurements across organisms, cells, tissues, populations, biomolecules and biological processes, including counts, concentrations, dimensions, biomass, growth, rates, viability, abundance, physiological quantities, assay responses, normalisation, sampling, calibration, uncertainty, reference conditions and provenance.

  SCOPE {
    organism_measurements
    cellular_measurements
    tissue_measurements
    biomolecular_measurements
    population_measurements
    physiological_measurements
    growth_and_development
    abundance_and_density
    viability_and_survival
    biological_rates
    assay_measurements
    microscopy
    sequencing_and_omics
    sampling
    normalisation
    calibration
    uncertainty_and_traceability
  }

  ENTITY BiologicalMeasurement {
    TYPE: MeasurementResult
    COMPONENTS:
      measurand
      biological_entity
      numerical_value
      unit
      method
      sample
      time
      location
      environment
      uncertainty
      provenance
  }

  ENTITY Count {
    TYPE: DiscreteQuantity
    SYMBOL: N
    DIMENSION: dimensionless

    EXAMPLES:
      cell_count
      organism_count
      colony_count
      sequence_read_count
      event_count
  }

  ENTITY NumberDensity {
    TYPE: CountPerVolumeQuantity
    SYMBOL: rho_N
    COMMON_UNITS:
      cells/mL
      organisms/L
      CFU/mL

    FORM:
      rho_N = N/V
      WHEN V != 0
  }

  ENTITY Biomass {
    TYPE: BiologicalMassQuantity
    SYMBOL: m_bio
    SI_UNIT: kilogram

    FORMS:
      wet_mass
      dry_mass
      ash_free_dry_mass
  }

  UNIT_SYSTEM {
    canonical_system: SI_where_applicable

    common_units:
      metre
      millimetre
      micrometre
      nanometre
      kilogram
      gram
      milligram
      mole
      mol/L
      g/L
      cells/mL
      CFU/mL
      copies/mL
      percent
      dimensionless_fraction

    RULE:
      unit MUST be interpreted_with_quantity_basis_and_entity_definition
  }

  COUNT_MODEL {
    count:
      N = number_of_defined_entities_or_events

    REQUIRE:
      entity_definition
      inclusion_criteria
      detection_method

    RULE:
      count_without_entity_definition_is_semantically_incomplete
  }

  DENSITY_MODEL {
    volume_density:
      rho_N = N/V

    areal_density:
      sigma_N = N/A

    linear_density:
      lambda_N = N/L

    RULE:
      volume_area_or_length_basis MUST be preserved
  }

  BIOMASS_MODEL {
    biomass_concentration:
      C_bio = m_bio/V

    RULE:
      wet_mass_and_dry_mass MUST_NOT be treated_as_equivalent
  }

  VIABILITY_MODEL {
    viable_fraction:
      f_viable = N_viable/N_total
      WHEN N_total != 0

    percent_viability:
      100*f_viable

    REQUIRE:
      viability_definition
      assay_method
      classification_threshold

    RULE:
      viability_is_assay_and_definition_dependent
  }

  GROWTH_MODEL {
    absolute_growth:
      delta_X = X_2-X_1

    growth_rate:
      dX/dt

    specific_growth_rate:
      mu = (1/X)*dX/dt

    exponential_growth:
      X(t) = X_0*exp(mu*t)

    doubling_time:
      t_d = ln(2)/mu
      WHEN mu > 0

    RULE:
      growth_growth_rate_and_specific_growth_rate MUST be distinguished
  }

  POPULATION_MODEL {
    exponential:
      N(t) = N_0*exp(r*t)

    logistic:
      dN/dt = r*N*(1-N/K)

    PARAMETERS:
      r = intrinsic_growth_rate
      K = carrying_capacity

    RULE:
      population_model_identity_and_assumptions MUST be preserved
  }

  SURVIVAL_MODEL {
    survival_function:
      S(t) = P(T_event > t)

    hazard:
      h(t) = -d(ln(S(t)))/dt

    RULE:
      survival_probability != hazard_rate
  }

  RATE_MODEL {
    generic:
      rate = change_in_quantity/change_in_time

    examples:
      heart_rate
      respiration_rate
      enzyme_rate
      division_rate
      migration_rate
      uptake_rate
      production_rate

    RULE:
      numerator_quantity_and_time_basis MUST be explicit
  }

  ENZYME_ACTIVITY_MODEL {
    reaction_rate:
      v = d(product_amount)/dt

    specific_activity:
      enzyme_activity/protein_mass

    Michaelis_Menten:
      v = V_max*[S]/(K_m+[S])

    RULE:
      assay_conditions_and_activity_units MUST be preserved
  }

  ASSAY_RESPONSE_MODEL {
    raw_response:
      detector_signal

    calibrated_quantity:
      biological_quantity = f(response)

    assays:
      absorbance
      fluorescence
      luminescence
      colorimetry
      immunoassay
      enzymatic_assay
      reporter_assay

    RULE:
      raw_signal MUST_NOT be treated_as_biological_quantity_without_valid_mapping
  }

  NORMALISATION_MODEL {
    denominators:
      sample_mass
      tissue_mass
      cell_count
      total_protein
      DNA_amount
      RNA_amount
      housekeeping_signal
      exposure_time
      area
      volume

    FORM:
      Q_norm = Q_raw/Q_reference
      WHEN Q_reference != 0

    RULE:
      normalisation_denominator MUST be preserved
  }

  FOLD_CHANGE_MODEL {
    fold_change:
      FC = Q_condition/Q_reference
      WHEN Q_reference != 0

    log2_fold_change:
      log2FC = log2(Q_condition/Q_reference)
      WHEN both_positive

    percent_change:
      100*(Q_condition-Q_reference)/Q_reference

    RULE:
      fold_change_percent_change_and_percentage_points_are_distinct
  }

  MICROSCOPY_MODEL {
    measurements:
      length
      area
      volume
      fluorescence_intensity
      object_count
      morphology

    REQUIRE:
      pixel_size
      magnification
      optical_resolution
      segmentation_method
      threshold
      region_of_interest

    RULE:
      pixel_measurements MUST be spatially_calibrated_before_physical_dimension_inference
  }

  FLOW_CYTOMETRY_MODEL {
    measurements:
      event_count
      forward_scatter
      side_scatter
      fluorescence
      population_fraction

    REQUIRE:
      gating_strategy
      compensation
      detector_settings
      controls

    RULE:
      population_fraction depends_on_declared_gating_definition
  }

  MOLECULAR_MEASUREMENT_MODEL {
    targets:
      DNA
      RNA
      protein
      metabolite

    reporting_bases:
      amount
      mass
      concentration
      copy_number
      relative_abundance
      normalised_expression

    RULE:
      molecular_measurement_basis MUST be explicit
  }

  PCR_MODEL {
    amplification:
      N_cycle = N_0*(1+E)^cycle

    ideal_efficiency:
      E = 1

    RULE:
      Ct_or_Cq != concentration_without_calibration_or_relative_quantification_model
  }

  SEQUENCING_MODEL {
    raw_read_count:
      assigned_sequence_count

    relative_abundance:
      reads_feature/total_eligible_reads

    normalisation:
      library_size
      feature_length
      model_based

    RULE:
      raw_counts_relative_abundance_and_normalised_expression_are_distinct
  }

  ECOLOGICAL_MODEL {
    absolute_abundance:
      number_of_individuals

    relative_abundance:
      N_i/sum(N_j)

    density:
      N_i/area_or_volume

    occupancy:
      detected_sample_units/total_sample_units

    RULE:
      abundance_density_and_occupancy_are_distinct
  }

  BIODIVERSITY_MODEL {
    richness:
      number_of_observed_taxa

    Shannon_index:
      H = -sum(p_i*ln(p_i))

    Simpson_family:
      requires_declared_formula

    RULE:
      diversity_index_definition MUST be declared
  }

  SAMPLING_MODEL {
    designs:
      random
      stratified
      systematic
      transect
      quadrat
      time_series
      replicate

    REQUIRE:
      sampling_frame
      sample_size
      location
      time
      inclusion_criteria

    RULE:
      sample_result MUST_NOT automatically_be_generalised_to_population_without_sampling_model
  }

  REPLICATE_MODEL {
    technical_replicate:
      repeated_measurement_of_same_sample

    biological_replicate:
      independently_sampled_biological_unit

    RULE:
      technical_and_biological_replicates MUST be distinguished
  }

  CALIBRATION_MODEL {
    examples:
      microscope_scale
      flow_cytometer_beads
      assay_standard_curve
      qPCR_standard_curve
      spectrophotometer
      balance

    generic:
      biological_quantity = f(instrument_response)

    REQUIRE:
      reference_standard
      valid_range
      calibration_date
      uncertainty

    RULE:
      calibration_model MUST match_method_and_quantity
  }

  RELATIONSHIPS {
    BiologicalMeasurement -> MEASURES -> BiologicalEntityOrProcess
    Count -> COUNTS -> DefinedBiologicalEntities
    NumberDensity -> RELATES -> CountAndVolume
    Biomass -> MEASURES -> BiologicalMass
    Viability -> RELATES -> ViableAndTotalCounts
    GrowthRate -> RELATES -> BiologicalChangeAndTime
    SpecificGrowthRate -> NORMALISES -> GrowthRateByCurrentQuantity
    AssayCalibration -> MAPS -> DetectorSignalToBiologicalQuantity
    SamplingDesign -> QUALIFIES -> PopulationInference
    Normalisation -> MAPS -> RawToNormalisedQuantity
    MeasurementUncertainty -> QUALIFIES -> BiologicalMeasurement
  }

  SEMANTIC_EQUIVALENCE {
    "cell density" ~= cell_number_per_volume WHEN declared_basis
    "relative abundance" ~= component_fraction WHEN declared_count_basis

    count != concentration
    count != density
    biomass != cell_count
    viability != survival_probability
    growth != growth_rate
    growth_rate != specific_growth_rate
    raw_assay_signal != calibrated_quantity
    technical_replicate != biological_replicate
    relative_abundance != absolute_abundance
    fold_change != percent_change
  }

  CONSTRAINTS {
    biological_entity_must_be_defined = true
    quantity_basis_must_be_defined = true
    unit_must_match_quantity = true
    sampling_context_should_be_preserved = true
    temporal_context_should_be_preserved = true
    spatial_context_should_be_preserved_when_relevant = true
    normalisation_denominator_must_be_defined = true
    assay_signal_requires_calibration_or_declared_relative_semantics = true
    technical_and_biological_replicates_must_be_distinguished = true
    uncertainty_should_include_sampling_and_measurement_components_when_relevant = true
  }

  MEASUREMENT_MODEL {
    methods:
      microscopy
      flow_cytometry
      spectrophotometry
      fluorimetry
      luminescence
      cell_counting
      culture_based_counting
      gravimetry
      PCR
      sequencing
      immunoassay
      chromatography
      physiological_monitoring
      ecological_sampling

    RECORD:
      measurand
      biological_entity
      entity_definition
      numerical_value
      unit
      quantity_basis
      sample_identifier
      sample_type
      sample_matrix
      spatial_location
      timestamp
      environmental_conditions
      developmental_or_life_stage
      measurement_method
      instrument
      assay_protocol
      calibration_model
      normalisation_method
      technical_replicates
      biological_replicates
      detection_limit
      uncertainty
      provenance

    UNCERTAINTY:
      biological_measurement = best_estimate +/- uncertainty
  }

  UNCERTAINTY_MODEL {
    sources:
      sampling_variability
      biological_variability
      sample_preparation
      instrument_calibration
      counting_statistics
      segmentation
      gating
      assay_response
      standard_curve
      normalisation
      environmental_variability
      operator_effect
      temporal_variability
      model_assumptions

    PROPAGATION:
      combined_biological_uncertainty
      <- sampling_biological_measurement_calibration_and_model_uncertainties
  }

  REASONING_RULES {
    IF count_known AND sample_volume != 0
      THEN number_density = count/sample_volume

    IF viable_count_and_total_count_known AND total_count != 0
      THEN viable_fraction = viable_count/total_count

    IF initial_and_final_quantity_known
      THEN absolute_change = final_quantity-initial_quantity

    IF quantity_change_known AND time_interval != 0
      THEN average_rate = quantity_change/time_interval

    IF exponential_growth_rate > 0
      THEN doubling_time = ln(2)/growth_rate

    IF raw_quantity_and_reference_known AND reference != 0
      THEN normalised_quantity = raw_quantity/reference

    IF condition_and_reference_quantities_known AND reference != 0
      THEN fold_change = condition/reference

    IF condition_and_reference_quantities_positive
      THEN log2_fold_change = log2(condition/reference)

    IF calibrated_assay_response_known
      THEN infer_biological_quantity = inverse_calibration(response)

    IF feature_reads_and_total_eligible_reads_known AND total_reads != 0
      THEN relative_abundance = feature_reads/total_reads
  }

  VALIDATION {
    CHECK biological_entity_identity
    CHECK measurand_definition
    CHECK unit_consistency
    CHECK quantity_basis
    CHECK sample_identity
    CHECK sampling_design
    CHECK spatial_and_temporal_context
    CHECK count_vs_density
    CHECK viability_definition
    CHECK growth_vs_rate
    CHECK normalisation_denominator
    CHECK raw_vs_calibrated_signal
    CHECK technical_vs_biological_replicates
    CHECK microscopy_scale_and_segmentation
    CHECK flow_cytometry_gating_and_compensation
    CHECK sequencing_normalisation
    CHECK calibration_range
    CHECK uncertainty_representation
  }

  CONFIDENCE {
    quantity_definition_confidence: 1.00
    unit_confidence: 1.00
    biological_entity_confidence: 0.99
    calibration_relationship_confidence: 0.98
    sampling_context_confidence: 0.97
    measurement_context_confidence: 0.97

    RULE:
      confidence decreases when entity definition, sample,
      measurement basis, sampling design, normalisation,
      calibration, replicate structure or uncertainty is missing or ambiguous
  }

  UPDATE_MODEL {
    ON new_measurement:
      identify_measurand
      identify_biological_entity
      identify_quantity_basis
      validate_unit
      attach_sample_identity
      attach_spatial_and_temporal_context
      attach_environmental_conditions
      identify_measurement_method
      apply_calibration_when_required
      preserve_raw_signal_or_count
      apply_declared_normalisation
      attach_replicate_structure
      attach_uncertainty
      update_biological_measurement_state

    ON sample_update:
      preserve_sample_provenance
      update_sample_type_matrix_or_stage
      update_preparation_history
      reevaluate_comparability

    ON calibration_revision:
      preserve_previous_calibration
      recompute_affected_results
      update_uncertainty
      update_confidence

    ON normalisation_revision:
      preserve_raw_quantity
      update_reference_quantity
      recompute_normalised_results
      preserve_previous_normalisation

    ON semantic_revision:
      preserve_previous_definition
      record_revision
      recompute_FLOW_HASH
  }

  AI_CONSUMPTION {
    canonical_domain: BiologicalMeasurements

    interpretation_order:
      identify_measurand
      identify_biological_entity
      identify_value
      identify_unit
      identify_quantity_basis
      identify_sample
      identify_spatial_temporal_and_environmental_context
      identify_measurement_method
      identify_raw_or_calibrated_status
      identify_normalisation
      identify_technical_and_biological_replicates
      identify_sampling_design
      identify_uncertainty
      normalize_units
      validate_semantics
      infer_biological_relationships

    ambiguity_controls:
      distinguish_count_from_density
      distinguish_biomass_from_cell_count
      distinguish_viability_from_survival_probability
      distinguish_growth_from_growth_rate
      distinguish_growth_rate_from_specific_growth_rate
      distinguish_raw_assay_signal_from_calibrated_quantity
      distinguish_technical_from_biological_replicates
      distinguish_absolute_from_relative_abundance
      distinguish_fold_change_from_percent_change
      preserve_entity_sample_method_normalisation_sampling_and_provenance_context
  }

  PROVENANCE {
    ontology_scope:
      mathematical_measurement_and_biological_quantity_semantics

    parent_path:
      Ontologies
      -> Mathematical Ontologies
      -> Measurement & Units Ontologies
      -> Biological Measurements Ontology

    authorship:
      Mark Higgins
      Sky (Recursive AI)

    site:
      https://kirethresearch.org
  }

  FLOW_HASH {
    INPUTS:
      canonical_domain
      ontology_path
      scope
      count_model
      density_model
      biomass_model
      viability_model
      growth_model
      population_model
      survival_model
      rate_model
      enzyme_activity_model
      assay_response_model
      normalisation_model
      fold_change_model
      microscopy_model
      flow_cytometry_model
      molecular_measurement_model
      PCR_model
      sequencing_model
      ecological_model
      biodiversity_model
      sampling_model
      replicate_model
      calibration_model
      relationships
      constraints
      measurement_model
      uncertainty_model
      reasoning_rules
      confidence_model
      update_model

    PURPOSE:
      deterministic_semantic_integrity_identifier

    RECOMPUTE_WHEN:
      ontology_definition_changes
      biological_quantity_model_changes
      entity_definition_changes
      sampling_model_changes
      assay_model_changes
      normalisation_model_changes
      calibration_model_changes
      measurement_model_changes
      constraint_model_changes
      reasoning_rule_changes
      unit_model_changes
  }

}

END FLOW