Sequence becomes a physical system
A base change is evaluated through its consequences for local state, structure, accessibility, and interaction—not treated only as a symbol or statistical feature.
Sequence analysis, variant interpretation, therapeutic candidate triage, and constrained design.
FluxMateria is developing a family of research-use modules for genomics, oligo therapeutics, resistance analysis, gene-editing workflows, and synthetic constructs.
FluxMateria's vision is to calculate what DNA and RNA will physically do—how a sequence pairs, folds, twists, opens, binds, fails, and can be improved—before a research team synthesizes and tests it.
Modern genomics can read sequences, compare them, and find statistical associations at enormous scale. The breakthrough is a physical computation layer between sequence and experiment: one that can explain why a change matters, evaluate alternatives, and guide the next design decision. What makes this revolutionary is the shift from correlating sequences with outcomes to calculating the physical causes that make one sequence behave differently from another.
A base change is evaluated through its consequences for local state, structure, accessibility, and interaction—not treated only as a symbol or statistical feature.
Sequence analysis, structural effects, molecular interaction, variant interpretation, candidate ranking, and redesign can be connected through one auditable computational chain.
Large candidate spaces can be narrowed, failure mechanisms identified, and constrained improvements proposed before the most expensive structural and experimental work begins.
Each workflow starts with a defined sequence, variant, target, or candidate set and returns outputs that a research team can review, compare, and test.
Map local sequence state, structural risk, opening tendency, and mutation sensitivity across DNA or RNA.
Compare reference and altered states, identify the physical delta, and report affected interactions and missing context.
Compare oligos, guides, primers, and probes before committing the full set to experimental testing.
Assess mutation-driven interaction changes, rank retained activity, and surface rescue or backup candidates.
The first four workflows are the current development focus. Later modules will advance only after their required inputs, outputs, benchmarks, and review boundaries are established.
Accept DNA or RNA sequences and return position-by-position maps of local state, structural risk, and mutation sensitivity.
Compare reference and altered sequences or targets and produce a research-use report of physical changes, affected interactions, confidence, and missing context.
Rank ASOs, siRNAs, guides, primers, and probes using target compatibility, mismatch response, self-structure, and off-target considerations.
Analyze mutated targets, compare candidates that retain interaction, explain resistance, and identify rescue or backup strategies for testing.
Generate alternatives under target, length, motif, chemistry, and manufacturability constraints, then return ranked designs and trade-offs.
Review mRNA, plasmid, vector-payload, and synthetic-construct risks and propose bounded changes that preserve declared functions and constraints.
Evaluate sequence-specific interaction geometry, mutation effects, competing states, interaction loss, and candidate redesign.
Analyze and eventually design promoters, UTRs, splice regions, terminators, and compact regulatory modules toward validated objectives.
Genome Physics projects will make the calculation scope, design constraints, output type, and evidence status explicit.
The page describes work in development, not currently available production modules or clinical capabilities.
Every solution is labeled by development stage. Planned capabilities are not presented as available software.
Claims advance only through frozen, scoped, independently scored tests and clearly reported limitations.
Review validation →Supported work remains bounded, research-use, and subject to purpose, target, output, and biosecurity controls.
Read the boundary →Early collaborations will help define useful inputs, decision-ready outputs, benchmarks, and prospective validation studies for the first modules.