Nucleic Acid Biology

				Natural Sciences
				Biology
				Molecular Biology
Element	Scope Category	Sub-Item	Definition	Nucleic Acid Biology
1. Domain	1.1 Scope of the Domain	Boundaries	The range of phenomena the science includes and excludes.	Nucleic Acid Biology studies the structure, chemistry, and functional behavior of DNA and RNA, including replication, repair, transcription, nucleotide modification, and nucleic acid conformations. It excludes protein-level mechanisms and organism-level genetics except where nucleic acids directly mediate them.
		Scale	The spatial, temporal, or organizational level at which the science operates (e.g., quantum, cellular, social, cosmic).	Operates at the atomic and molecular scale: nucleotides, bases, phosphodiester linkages, helices, RNA secondary structures, and enzyme–nucleic acid interactions across picosecond chemistry through cell-cycle timescales.
	1.2 Ontological Commitments	Entities	The kinds of things assumed to exist within the domain (particles, organisms, agents, fields, etc.).	DNA, RNA, nucleotides, nitrogenous bases, phosphates, chromatin structures, replication forks, polymerases, helicases, ligases, RNA-processing complexes, ribonucleoproteins, and repair intermediates.
		Properties	The fundamental attributes these entities possess (mass, charge, genotype, preference, etc.).	Sequence identity, base-pairing specificity, chemical reactivity, helical form (A/B/Z), methylation status, folding potential, thermodynamic stability, susceptibility to damage, and capacity to encode information.
		Categories	The basic ontological types used to classify domain elements (substances, processes, relations, structures).	DNA vs RNA, coding vs noncoding sequences, primary/secondary/tertiary structures, replication vs transcription pathways, modification types, damage categories, and enzyme–nucleic acid interaction classes.
	1.3 State-Variables	Variables	The measurable or definable properties that describe system conditions.	Nucleotide sequence, GC content, base-pairing stability, methylation levels, supercoiling density, transcription rate, replication fork velocity, mutation frequency, and RNA folding states.
		Parameterization	How variables encode and represent the system’s state.	State represented by sequence data, epigenetic modification maps, chromatin accessibility, folding-energy profiles, structural annotations, and quantitative assays such as qPCR Ct values or sequencing depth.
	1.4 Admissible Idealizations	Simplifications	Conceptual reductions used to make the domain tractable (point masses, rational agents, perfect gases).	DNA treated as ideal B-form helix; RNA folding approximated by minimum-free-energy models; lesions treated as uniform; enzymatic pathways reduced to simplified kinetic cycles; chromatin context ignored.
		Validity Conditions	The limits and contexts in which idealizations hold or break down.	Idealizations break down when sequence context alters geometry, RNA forms complex tertiary folds, chromatin compaction restricts access, or enzyme kinetics shift under crowding or stress.
	1.5 Domain Assumptions	Structural Assumptions	Background ontological stances such as determinism, continuity, randomness, discreteness.	Assumes stable base-pairing rules, deterministic enzyme-substrate interactions, chemical continuity of nucleic acid reactions, predictable thermodynamic folding, and reliable information storage.
		Implicit Commitments	Unstated but necessary assumptions that shape the field’s conceptual structure.	Assumes nucleic acids remain chemically stable, sequences encode meaningful biological information, modifications have interpretable roles, and enzymes act with consistent specificity.
	1.6 Internal Coherence Requirements	Consistency	The demand that domain concepts do not contradict one another.	Concepts of sequence, structure, replication, transcription, and repair must be chemically and thermodynamically consistent without contradiction.
		Compatibility	The requirement that entities, variables, and assumptions fit together into a unified descriptive framework.	Entities (DNA, RNA, enzymes), variables (sequence, structure), and assumptions (specificity, stability) must integrate into a unified chemical and informational framework.
2. Evidence Layer	2.1 Observable Phenomena	Observables	The aspects of the domain that can produce detectable signals accessible to measurement.	Detectable features such as nucleotide sequences, base-pairing patterns, methylation status, chromatin accessibility, replication fork movement, transcriptional activity, RNA structures, and nucleic acid damage signatures.
		Detection Limits	The boundaries of what can be resolved or sensed by current instruments or methods.	Resolution thresholds for sequencing depth, single-molecule detection sensitivity, minimum detectable methylation changes, limits of qPCR amplification, minimal observable structural variation, and bounds imposed by imaging resolution.
	2.2 Measurement Systems	Units	Standardized quantifications (meters, seconds, volts, decibels, dollars, etc.) necessary for consistent comparison.	Quantifications using base units (nucleotides, base pairs), concentration (nM, µM), reaction rates (s⁻¹), sequencing depth (reads), fluorescence intensity, Ct values, coverage percentages, and fold-change measures.
		Instruments	Devices and tools (microscopes, spectrometers, sensors, surveys, detectors) used to produce measurements.	Sequencers, PCR machines, qPCR systems, fluorescence microscopes, confocal microscopes, FISH setups, spectrophotometers (A260/A280), gel electrophoresis systems, capillary electrophoresis, nanopore sensors, and single-molecule imaging platforms.
	2.3 Operational Definitions	Definitions	Terms defined by specific measurement procedures, ensuring empirical clarity.	Operational definitions of sequence identity, methylation percentage, transcription rate, replication timing, chromatin openness, and RNA structure based on assay-specific measurement protocols.
		Procedures	The explicit steps required to perform a measurement in a reproducible way.	Standardized steps such as DNA/RNA extraction, library preparation, PCR cycling, electrophoretic separation, hybridization protocols, enzymatic assays, sequencing workflows, and structural probing methods.
	2.4 Data Acquisition	Protocols	Formal processes for gathering data under controlled or standardized conditions.	Controlled processes including sequencing runs, qPCR cycles, ChIP protocols, bisulfite conversion, RNA structure probing, pull-down assays, and time-course measurements of replication or transcription.
		Sampling	Rules determining which subset of the domain is measured and how representative it is.	Rules for selecting genomic regions, transcript subsets, structural regions, cell populations, time points, or molecular fractions to ensure representativeness and adequate biological replication.
	2.5 Data Character & Format	Data Types	The form raw evidence takes (time series, spectra, images, counts, qualitative records).	Sequence reads, base-calling data, methylation maps, electrophoretic band patterns, fluorescence intensities, structural reactivity profiles, expression levels, and chromatin accessibility matrices.
		Resolution	The granularity or precision with which data is captured.	Base-pair resolution in sequencing, single-nucleotide detection of modifications, temporal resolution of replication/transcription kinetics, spatial resolution of FISH or imaging, and signal-to-noise thresholds.
	2.6 Reliability & Calibration	Calibration	Adjustment procedures ensuring instruments produce accurate results.	Adjustment of sequencers, PCR machines, fluorescence detectors, electrophoresis systems, and imaging tools using reference standards, spike-in controls, calibrant sequences, and known molecules.
		Error Characterization	Identification and quantification of noise, uncertainty, bias, and measurement error.	Identification and quantification of noise from sequencing errors, PCR bias, amplification artifacts, fluorescence drift, mapping ambiguity, structural misfolding signals, sampling error, and instrument-specific bias.
3. Structural Layer	3.1 Patterns & Regularities	Laws / Relations	Stable, repeatable patterns governing how observables behave across conditions.	Base-pairing rules (Watson–Crick and permissible noncanonical pairs), complementarity, directionality (5’→3’), semiconservative replication, transcriptional initiation rules, sequence–structure relationships, and modification–function correlations.
		Invariants	Quantities or properties that remain constant under transformations (symmetries, conservation laws).	Conservation of sequence integrity through replication fidelity, preservation of base-pair complementarity, maintenance of methylation patterns across cell divisions, stable structural motifs in RNA, and conserved catalytic functions of nucleic acid–processing enzymes.
	3.2 Causal Architecture	Mechanisms	Underlying processes or structures that produce the observed regularities.	Mechanistic processes including template-directed polymerization, helicase-mediated unwinding, repair cascades, base-excision and nucleotide-excision pathways, RNA folding dynamics, and chromatin-mediated accessibility regulation.
		Pathways	Organized sequences of interactions forming a causal chain or network.	Causal chains such as replication initiation → fork progression → proofreading → ligation; or transcription initiation → elongation → RNA processing → export; or damage detection → repair enzyme recruitment → excision/synthesis → restoration.
	3.3 Theoretical Vocabulary	Concepts	Core terms that encode the domain’s structure (force, gene, equilibrium, field).	Key terms include complementarity, fidelity, mutation, epigenetic modification, supercoiling, chromatin accessibility, transcription units, replication origins, RNA secondary structure, and repair lesions.
		Classifications	Taxonomies, categories, or typologies that organize entities and relations.	Taxonomies including DNA vs RNA types, coding vs noncoding regions, repair pathway categories (BER, NER, MMR), replication origin classes, RNA structure classes, modification types (methylation, acetylation, oxidation), and chromatin states.
	3.4 Formal Representations	Equations	Mathematical constructs expressing laws, relations, or mechanisms.	Kinetic rate equations for polymerase activity, thermodynamic equations for base-pair stability and RNA folding energies, Michaelis–Menten approximations for nucleic acid enzymes, and probabilistic models of mutation rates.
		Models	Structured representations—mathematical, computational, or conceptual—used to predict and explain phenomena.	Structural models of DNA helices, RNA folding models (minimum free-energy, ensemble-based), replication-fork models, stochastic transcription models, chromatin accessibility models, and computational sequence evolution models.
	3.5 Idealized Structures	Simplified Models	Purposeful abstractions that capture essential dynamics while omitting irrelevant detail.	Idealized helices, minimal-energy RNA structures, simplified replication forks, uniform damage-site models, coarse-grained chromatin loops, and abstracted enzyme–nucleic acid interaction schemes.
		Limit Conditions	Regimes where specific models or approximations hold (classical vs. quantum, linear vs. nonlinear).	Approximations hold under stable physiological conditions, moderate ionic strength, standard temperatures, intact chromatin architecture, and predictable enzyme kinetics; they break down under stress, unusual sequences, or extreme structural perturbations.
	3.6 Integrative Frameworks	Unifying Theories	Higher-order structures that connect disparate laws or mechanisms under a coherent whole.	The central dogma (DNA→RNA→protein), molecular information flow, sequence–structure–function relationships, and genome integrity frameworks unifying replication, transcription, repair, and chromatin dynamics.
		Interdisciplinary Links	Points where the theory connects to adjacent sciences or larger explanatory systems.	Connections to structural biology, biochemistry, genetics, epigenomics, biophysics, computational biology, and evolutionary theory through shared principles of molecular interactions, information encoding, and chemical energy landscapes.
4. Method Layer	4.1 Inquiry Design	Experimental Design	Structured plans for manipulating variables to test causal claims.	Controlled manipulation of nucleic acid variables through PCR, mutagenesis, enzymatic assays, structural probing, CRISPR editing, replication or transcription perturbations, and targeted chemical modification.
		Observational Design	Systematic approaches for gathering non-manipulated data (surveys, field studies, natural experiments).	Non-manipulative approaches such as sequencing native DNA/RNA, observing natural replication or transcription dynamics, measuring spontaneous mutation patterns, mapping chromatin states, or profiling epigenetic marks.
	4.2 Testing & Validation	Hypothesis Testing	Procedures for evaluating whether evidence supports or contradicts specific claims.	Evaluating proposed mechanisms—e.g., testing whether a base modification alters transcription, whether a mutation affects folding, or whether a repair enzyme targets specific lesions—using quantitative molecular assays.
		Replication	The requirement that results be independently reproducible under similar conditions.	Reproducing sequencing runs, PCR amplifications, structural probing assays, enzyme-kinetic measurements, or chromatin-accessibility experiments across multiple replicates and independent laboratories.
	4.3 Inference & Evaluation	Statistical Inference	Rules for drawing conclusions from noisy or incomplete data.	Inferring sequence effects, modification impacts, or replication/transcription changes from noisy or high-throughput data using statistical models, confidence intervals, p-values, error propagation, or Bayesian frameworks.
		Model Comparison	Criteria (fit, simplicity, predictive accuracy, robustness) used to evaluate competing models.	Evaluating folding models, kinetic models, mutation models, or chromatin-accessibility models based on fit, predictive accuracy, thermodynamic plausibility, computational tractability, and experimental validation.
	4.4 Error Management	Error Analysis	Identification and quantification of random and systematic errors.	Quantifying sequencing errors, PCR amplification bias, base-calling inaccuracies, mapping ambiguity, fluorescence noise, structural misfold predictions, and systematic variability in enzymatic assays.
		Bias Control	Methods for minimizing subjective, instrumental, or procedural biases.	Minimizing biases through calibrated controls, randomized sample processing, enzyme-fidelity checks, spike-in standards, balanced library preparation, and standardized imaging or sequencing protocols.
	4.5 Adjudication & Revision	Peer Scrutiny	Collective evaluation of claims through critique, review, and debate.	Independent evaluation of data interpretation, sequencing pipelines, structural models, enzyme mechanisms, and genome-mapping claims through peer review and collaborative comparison.
		Theory Revision	Procedures for modifying, replacing, or discarding models based on new evidence.	Updating mechanistic models of replication, transcription, repair, folding, or modification when new evidence contradicts existing assumptions or reveals previously unknown pathways or structural states.
	4.6 Integrity Conditions	Transparency	Requirements to disclose methods, data, assumptions, and limitations.	Full reporting of extraction procedures, library workflows, sequencing parameters, structural-probing conditions, enzyme details, data-processing pipelines, and assumptions behind model selection.
		Ethical Standards	Norms ensuring responsible conduct in experimentation, data handling, and publication.	Ensuring proper conduct in genomic experiments, accurate reporting of sequences and modifications, responsible handling of genetic information, and avoidance of data manipulation or selective reporting.