Every layer of the cell, read as data.
This guide walks from the chemistry of DNA to the algorithms that turn sequencers, mass spectrometers and microscopes into biological knowledge. For each omics layer it explains what is measured, why it matters, how the data are processed, which tools do each step, what independent benchmarks found, and which questions are still open.
The layers, top to bottom
Information flows down this stack, from the relatively stable genome to the fast-changing metabolome. The bar shows roughly how dynamic each layer is (how fast it changes within a cell or person). Click a layer to open its chapter.
How to read the tool tables
Every chapter lists the main tools for that layer. Each tool carries two kinds of "level", because people mean both when they ask about a tool's level.
Analysis stage
Primary Raw instrument signal to usable reads or spectra: base calling, demultiplexing, signal processing.
Secondary Reads or spectra to features: alignment, quantification, variant calling, peak calling, identification.
Tertiary Features to biology: statistics, differential analysis, annotation, networks, integration, interpretation.
Skill level
●●● Entry: GUI, web server or one-command pipeline; sensible defaults.
●●● Intermediate: scripting in R or Python, choosing parameters, understanding the model.
●●● Advanced: method-level understanding, HPC or GPU, custom models, many parameters that change the answer.
Callouts
The concept to remember.
What independent comparisons found.
An open problem, often a thesis topic.
A common way to get it wrong.
Suggested routes through the guide
New to biology
≈ 3 weeksNew to computation
≈ 6 weeksTool versions and benchmark rankings change quickly. Benchmarks are cited by first author, year and journal; each citation links to a PubMed search so you can read the original and check for newer work. When a statement is a judgement rather than a published result, the text says so.