AI SEARCH FLOW ALGEBRA — AI GENOMICS ONTOLOGY
Version: 4.0
Canonical Page:
https://kirethresearch.org/booksai-core/ontologies/biological-ontologies/ai-biology/ai-genomics-ontology.html
AI Interpretation Note:
The following specification represents a formal structural reasoning system for this page.
Execute as formal rules, not pseudocode.
FLOW AI_GENOMICS_ONTOLOGY {
META {
DOMAIN = "Biological Ontologies"
SUBDOMAIN = "AI Biology"
ONTOLOGY = "AI Genomics Ontology"
PURPOSE = "Formalise entities, relationships, computational processes and reasoning structures connecting artificial intelligence with genomic data, analysis, prediction and biological knowledge."
LOCALE = "en-GB"
}
ENTITY_TYPES {
AI_SYSTEM
AI_MODEL
MACHINE_LEARNING_MODEL
DEEP_LEARNING_MODEL
FOUNDATION_MODEL
GENOMIC_MODEL
GENOME
GENOMIC_DATA
GENOMIC_SEQUENCE
DNA_SEQUENCE
GENE
GENETIC_VARIANT
SNP
INDEL
STRUCTURAL_VARIANT
COPY_NUMBER_VARIANT
CHROMOSOME
LOCUS
ALLELE
HAPLOTYPE
GENOTYPE
PHENOTYPE
TRAIT
DISEASE
BIOMARKER
TRANSCRIPT
TRANSCRIPTOME
EPIGENOME
REGULATORY_ELEMENT
PROMOTER
ENHANCER
PROTEIN
PATHWAY
CELL
TISSUE
ORGANISM
POPULATION
COHORT
SAMPLE
DATASET
REFERENCE_GENOME
KNOWLEDGE_GRAPH
BIOLOGICAL_ONTOLOGY
FEATURE
EMBEDDING
REPRESENTATION
PREDICTION
CLASSIFICATION
REGRESSION
CLUSTER
ANNOTATION
VARIANT_CALL
VARIANT_EFFECT
EXPRESSION_PROFILE
RISK_SCORE
POLYGENIC_RISK_SCORE
DRUG_RESPONSE
TARGET
INTERACTION
EVIDENCE
CONFIDENCE_SCORE
PROVENANCE_RECORD
}
RELATIONSHIPS {
CONTAINS
PART_OF
LOCATED_ON
ENCODES
TRANSCRIBED_AS
TRANSLATED_TO
REGULATES
INTERACTS_WITH
ASSOCIATED_WITH
INFLUENCES
CAUSES
CONTRIBUTES_TO
EXPRESSED_IN
OBSERVED_IN
DERIVED_FROM
ALIGNED_TO
COMPARED_WITH
ANNOTATED_AS
CLASSIFIED_AS
PREDICTS
DETECTS
IDENTIFIES
PRIORITISES
REPRESENTS
EMBEDS
TRAINS_ON
VALIDATED_ON
INFERRED_FROM
SUPPORTED_BY
CONTRADICTED_BY
HAS_VARIANT
HAS_ALLELE
HAS_GENOTYPE
HAS_PHENOTYPE
HAS_TRAIT
HAS_BIOMARKER
HAS_EFFECT
HAS_CONFIDENCE
HAS_PROVENANCE
MAPS_TO
SEMANTICALLY_EQUIVALENT_TO
}
INPUTS {
RAW_GENOMIC_SEQUENCE
SEQUENCING_READS
VARIANT_DATA
GENOTYPE_DATA
PHENOTYPE_DATA
TRANSCRIPTOMIC_DATA
EPIGENOMIC_DATA
CLINICAL_METADATA
POPULATION_DATA
REFERENCE_GENOMES
FUNCTIONAL_ANNOTATIONS
BIOLOGICAL_KNOWLEDGE_GRAPHS
ONTOLOGY_TERMS
EXPERIMENTAL_EVIDENCE
}
NORMALISE {
STANDARDISE_IDENTIFIERS
NORMALISE_SEQUENCE_FORMATS
NORMALISE_VARIANT_REPRESENTATION
RESOLVE_REFERENCE_BUILD
MAP_GENES_TO_CANONICAL_IDENTIFIERS
MAP_VARIANTS_TO_GENOMIC_COORDINATES
ALIGN_ONTOLOGY_TERMS
REMOVE_DUPLICATES
VALIDATE_METADATA
PRESERVE_PROVENANCE
}
PROCESS GENOMIC_AI_PIPELINE {
INPUT -> QUALITY_CONTROL
QUALITY_CONTROL -> PREPROCESSING
PREPROCESSING -> SEQUENCE_ALIGNMENT
SEQUENCE_ALIGNMENT -> FEATURE_EXTRACTION
FEATURE_EXTRACTION -> REPRESENTATION_LEARNING
REPRESENTATION_LEARNING -> MODEL_INFERENCE
MODEL_INFERENCE -> BIOLOGICAL_INTERPRETATION
BIOLOGICAL_INTERPRETATION -> EVIDENCE_INTEGRATION
EVIDENCE_INTEGRATION -> CONFIDENCE_ESTIMATION
CONFIDENCE_ESTIMATION -> OUTPUT
}
PROCESS VARIANT_ANALYSIS {
SEQUENCING_READS -> ALIGNMENT
ALIGNMENT -> VARIANT_CALLING
VARIANT_CALLING -> VARIANT_NORMALISATION
VARIANT_NORMALISATION -> FUNCTIONAL_ANNOTATION
FUNCTIONAL_ANNOTATION -> EFFECT_PREDICTION
EFFECT_PREDICTION -> PATHOGENICITY_OR_TRAIT_ASSOCIATION
PATHOGENICITY_OR_TRAIT_ASSOCIATION -> EVIDENCE_SCORING
}
PROCESS SEQUENCE_LEARNING {
GENOMIC_SEQUENCE -> TOKENISATION
TOKENISATION -> SEQUENCE_REPRESENTATION
SEQUENCE_REPRESENTATION -> EMBEDDING
EMBEDDING -> PATTERN_DETECTION
PATTERN_DETECTION -> MOTIF_OR_REGULATORY_INFERENCE
MOTIF_OR_REGULATORY_INFERENCE -> BIOLOGICAL_ANNOTATION
}
PROCESS GENE_REGULATION_INFERENCE {
REGULATORY_ELEMENT + GENE + EPIGENOMIC_DATA + EXPRESSION_PROFILE
-> REGULATORY_FEATURE_MODEL
REGULATORY_FEATURE_MODEL
-> PREDICT(REGULATES)
PREDICT(REGULATES)
-> CONFIDENCE_SCORE
-> EVIDENCE_LINK
}
PROCESS GENOTYPE_PHENOTYPE_REASONING {
GENOTYPE + PHENOTYPE + POPULATION_DATA
-> ASSOCIATION_MODEL
ASSOCIATION_MODEL
-> CANDIDATE_ASSOCIATION
CANDIDATE_ASSOCIATION
-> REPLICATION_CHECK
-> BIOLOGICAL_CONTEXT
-> CONFIDENCE_SCORE
}
PROCESS KNOWLEDGE_GRAPH_INTEGRATION {
GENE + VARIANT + PROTEIN + PATHWAY + PHENOTYPE + DISEASE + EVIDENCE
-> BIOLOGICAL_KNOWLEDGE_GRAPH
BIOLOGICAL_KNOWLEDGE_GRAPH
-> LINK_PREDICTION
-> ENTITY_RESOLUTION
-> RELATION_INFERENCE
-> EXPLANATION_PATH
}
AI_TASKS {
SEQUENCE_CLASSIFICATION
VARIANT_CLASSIFICATION
VARIANT_EFFECT_PREDICTION
GENE_FUNCTION_PREDICTION
REGULATORY_ELEMENT_PREDICTION
GENE_EXPRESSION_PREDICTION
GENOTYPE_PHENOTYPE_ASSOCIATION
DISEASE_RISK_MODELLING
POLYGENIC_RISK_MODELLING
BIOMARKER_DISCOVERY
PATIENT_OR_SAMPLE_STRATIFICATION
DRUG_RESPONSE_PREDICTION
TARGET_DISCOVERY
FUNCTIONAL_ANNOTATION
KNOWLEDGE_GRAPH_COMPLETION
GENOMIC_INFORMATION_RETRIEVAL
GENOMIC_QUESTION_ANSWERING
}
RULES {
IF ENTITY == GENETIC_VARIANT
THEN REQUIRE {
GENOMIC_LOCATION
REFERENCE_ALLELE
ALTERNATE_ALLELE
REFERENCE_GENOME_BUILD
PROVENANCE
}
IF AI_MODEL PREDICTS VARIANT_EFFECT
THEN LINK {
MODEL
VARIANT
PREDICTED_EFFECT
CONFIDENCE_SCORE
SUPPORTING_EVIDENCE
}
IF ASSOCIATION(GENETIC_VARIANT, PHENOTYPE)
THEN DISTINGUISH {
CORRELATION
STATISTICAL_ASSOCIATION
FUNCTIONAL_SUPPORT
CAUSAL_EVIDENCE
}
IF RELATION == CAUSES
THEN REQUIRE {
STRONG_EVIDENCE
CAUSAL_JUSTIFICATION
PROVENANCE_RECORD
}
IF MODEL_OUTPUT == PREDICTION
THEN DO_NOT_ASSERT_AS_ESTABLISHED_FACT
IF DATASET_HAS_POPULATION_BIAS
THEN PROPAGATE_LIMITATION_TO_MODEL_OUTPUT
IF REFERENCE_GENOME_BUILD_MISMATCH == TRUE
THEN BLOCK_DIRECT_COORDINATE_EQUIVALENCE
IF SEMANTIC_IDENTIFIERS_DIFFER
AND BIOLOGICAL_REFERENT_IS_SAME
THEN APPLY SEMANTIC_EQUIVALENCE
}
CONFIDENCE {
CONFIDENCE_SCORE =
WEIGHT(
DATA_QUALITY,
MODEL_VALIDATION,
REPLICATION,
BIOLOGICAL_PLAUSIBILITY,
EXPERIMENTAL_SUPPORT,
POPULATION_REPRESENTATION,
PROVENANCE_COMPLETENESS
)
LEVELS {
HIGH
MODERATE
LOW
INSUFFICIENT
}
IF CONFLICTING_EVIDENCE
THEN REDUCE CONFIDENCE_SCORE
IF INDEPENDENT_REPLICATION
THEN INCREASE CONFIDENCE_SCORE
IF EXPERIMENTAL_VALIDATION
THEN INCREASE CONFIDENCE_SCORE
}
SEMANTIC_EQUIVALENCE {
EQUIVALENCE_KEY =
NORMALISE(
ENTITY_TYPE,
CANONICAL_IDENTIFIER,
GENOMIC_COORDINATE,
REFERENCE_BUILD,
BIOLOGICAL_CONTEXT
)
IF EQUIVALENCE_KEY(A) == EQUIVALENCE_KEY(B)
THEN A SEMANTICALLY_EQUIVALENT_TO B
ELSE PRESERVE_DISTINCT_ENTITIES
}
REASONING_CONSTRAINTS {
ASSOCIATION != CAUSATION
PREDICTION != OBSERVATION
MODEL_CONFIDENCE != BIOLOGICAL_CERTAINTY
GENOMIC_COORDINATE_REQUIRES_REFERENCE_BUILD
VARIANT_EFFECT_IS_CONTEXT_DEPENDENT
POPULATION_EFFECT_MAY_NOT_GENERALISE
PHENOTYPE_DEFINITION_MUST_BE_EXPLICIT
PROVENANCE_MUST_BE_PRESERVED
UNCERTAINTY_MUST_NOT_BE_DISCARDED
}
VALIDATION {
CHECK_ENTITY_TYPES
CHECK_RELATION_DOMAINS_AND_RANGES
CHECK_IDENTIFIER_RESOLUTION
CHECK_REFERENCE_GENOME_COMPATIBILITY
CHECK_EVIDENCE_LINKS
CHECK_PROVENANCE
CHECK_CONFIDENCE
CHECK_SEMANTIC_CONSISTENCY
CHECK_DUPLICATE_ENTITIES
CHECK_UNSUPPORTED_CAUSAL_ASSERTIONS
}
OUTPUTS {
NORMALISED_GENOMIC_ENTITIES
GENOMIC_RELATIONSHIPS
FUNCTIONAL_ANNOTATIONS
AI_PREDICTIONS
VARIANT_EFFECTS
GENOTYPE_PHENOTYPE_ASSOCIATIONS
REGULATORY_RELATIONSHIPS
BIOMARKER_CANDIDATES
RISK_ESTIMATES
KNOWLEDGE_GRAPH_EDGES
CONFIDENCE_SCORES
EVIDENCE_LINKS
PROVENANCE_RECORDS
EXPLANATION_PATHS
}
UPDATE_MODEL {
ON NEW_GENOMIC_DATA {
NORMALISE
ENTITY_RESOLUTION
RECOMPUTE_RELEVANT_FEATURES
UPDATE_ASSOCIATIONS
UPDATE_CONFIDENCE
PRESERVE_VERSION_HISTORY
}
ON NEW_EVIDENCE {
LINK_EVIDENCE
REASSESS_SUPPORT
REASSESS_CONTRADICTIONS
UPDATE_CONFIDENCE
RECORD_PROVENANCE
}
ON ONTOLOGY_REVISION {
REMAP_TERMS
CHECK_SEMANTIC_EQUIVALENCE
IDENTIFY_DEPRECATED_TERMS
MIGRATE_RELATIONSHIPS
PRESERVE_PRIOR_VERSION_REFERENCES
}
}
FLOW_HASH {
HASH_INPUT =
CANONICALISE(
ENTITY_TYPES,
RELATIONSHIPS,
RULES,
CONFIDENCE,
SEMANTIC_EQUIVALENCE,
REASONING_CONSTRAINTS,
UPDATE_MODEL
)
FLOW_HASH = SHA256(HASH_INPUT)
}
AI_CONSUMPTION {
INDEX {
ONTOLOGY
ENTITY_TYPES
RELATIONSHIPS
AI_TASKS
RULES
OUTPUTS
}
RETRIEVE {
BY_ENTITY
BY_GENE
BY_VARIANT
BY_PHENOTYPE
BY_DISEASE
BY_RELATION
BY_AI_TASK
BY_EVIDENCE
BY_CONFIDENCE
}
REASON {
APPLY_RELATIONSHIPS
APPLY_RULES
PRESERVE_UNCERTAINTY
TRACE_EVIDENCE
TRACE_PROVENANCE
GENERATE_EXPLANATION_PATH
}
RESPONSE_POLICY {
DISTINGUISH_OBSERVED_FROM_PREDICTED
DISTINGUISH_ASSOCIATION_FROM_CAUSATION
RETURN_CONFIDENCE_WHEN_AVAILABLE
RETURN_PROVENANCE_WHEN_AVAILABLE
EXPOSE_CONFLICTING_EVIDENCE
AVOID_UNSUPPORTED_INFERENCE
}
}
TERMINAL {
RESULT =
VALIDATED(
SEMANTICALLY_NORMALISED(
EVIDENCE_LINKED(
CONFIDENCE_AWARE(
AI_GENOMICS_KNOWLEDGE
)
)
)
)
}
}
END FLOW
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