Mermaid flowcharts for perturbation design: diagrams-as-code, curated databases, and the E. coli lac operon as a worked example

Planning genetic, pharmacological, or nutritional perturbations is easier when the investigator can state,
in advance, which molecular levers are plausible and which readouts would discriminate competing
mechanisms. Logic-style flowcharts - authored as diagrams-as-code (here using Mermaid markdown) 
provide a lightweight, versionable complement to pathway databases, genome browsers, and
machine-learning predictors. This methods paper distills a seminar-tested workflow for a general
research audience: we motivate text-based diagrams in wet-lab and computational pipelines; we
compare three deliberately different encodings of the classical Escherichia coli lactose (lac) operon - a
literature-first logic diagram with explicit Boolean-style gates, a RegulonDB-emphasis regulatory
wiring diagram without those gates, and a hybrid diagram that retains interpretive logic while adding
database-grounded entities (notably explicit lacI expression); we explain why the full two-input induction
condition (inducer present and catabolite repression relieved) appears only in some encodings; and we
recommend layered hybridization (regulatory backbone + literature logic + identifier and parts audits)
instead of naively merging incompatible ontologies. No bespoke software is required beyond ordinary
LLM access, Mermaid rendering, and public databases.