Mass-spectrometry-based proteomics: peptide/protein identification (DDA, DIA), quantification, PTM analysis, and statistical comparisons across conditions.
A baseline path through this sector with milestones, prerequisites, and concrete projects. Click Personalize this roadmap above to have the AI tailor pace, depth, and resources to your background and goals.
Build the conceptual and quantitative base needed to read papers and follow tutorials in the sector.
Walk through a published tutorial in FragPipe + MSstats and reproduce its results on the provided sample data.
Deliverable: GitHub repo with a Jupyter/Quarto notebook, environment.yml, and README
Learn the standard analytical stack of the sector and the canonical public datasets used by professionals.
Pick one study from PRIDE / MassIVE public datasets, reproduce the headline result, and write a short technical note on what you found.
Deliverable: GitHub repo + 3-page PDF write-up
Move from tutorials to original analyses on real questions. Start showing your work publicly.
Re-process a PRIDE DIA dataset end-to-end and reproduce the headline differential-abundance result with a clean stats report.
Deliverable: Reproducible repo + volcano plot + 4-page methods/results
Package your work, target real roles, and prepare to interview in the sector.
Curate 2–3 of your strongest sector projects into a portfolio site with clear case-study writeups, plus a 1-page CV tailored to the target role.
Deliverable: Live portfolio URL + PDF CV + cover letter template
Verified, canonical resources from the official providers in this sector. The AI roadmap builder draws from this same library when it personalizes your roadmap.
Runs MaxQuant / FragPipe / DIA-NN pipelines and downstream statistics on MS data.
Builds reproducible proteomics workflows and integrates them with multi-omics cohorts.
Answer a short profile and the AI builder will tailor every phase — pace, hours, tools, and resources — to your background and goals in this sector.
Build my personalized roadmap