
A single measurement rarely explains a phenotype. When a strain behaves differently, the cause may sit in its genome, in how much of a given protein it makes, in what it secretes, or in the rate at which it consumes a substrate. So we strive to measure all of it, on the same strains and under the same conditions. That is our definition of systems biology. Genome resequencing forms the core: standardized workflows take raw reads to annotated variants, with automated detection of point mutations, insertions and deletions, mobile-element movements, and larger structural rearrangements, covering the full range of changes a genome actually undergoes rather than just the ones easiest to call. Around that core we run transcriptomics, proteomics, and exometabolomics at experiment scale, together with quantitative phenomic measurements of growth, uptake, and secretion. Because these workflows are standardized rather than assembled per project, a measurement made in one experiment means the same thing as the equivalent measurement made three years earlier in a different organism, which is the precondition for comparing anything at all.
Comparability only becomes useful once the data is structured, which is what ALEdb provides. Our contribution to the field's data infrastructure, ALEdb is an open, queryable database holding evolution experiments together with their genetic changes, the conditions that produced them, and the phenotypes that resulted, with each measurement linked to its experimental context rather than deposited as an isolated file. That structure is what makes system-wide questions answerable: the same mutation can be traced across studies, conditions, and organisms, and expression or metabolite changes can be examined for the conditions that reliably provoke them. It also makes the accumulated record directly usable by statistical, machine learning, and AI methods, which require exactly this kind of labeled, standardized input and rarely have access to it in biology. We release data in FAIR-compliant form so that others can use it the way we do: reusable, not merely publishable, though we recommend that as well.


