Cortessa helps researchers, labs, and early-stage biotech teams analyze data, communicate findings clearly, and present their work credibly online — backed by published research and open-source tools with real usage.
We don't sell templates or generic execution. We sell judgment — the difference between an analysis that looks right and one that is right.
Each module can stand alone — but most clients start with analysis, and grow into the rest once trust is established.
RNA-seq and NGS analysis, statistics, and publication-ready figures — with a written interpretation, not just a script output.
Precise, defensible writing that replaces vague claims with language a reviewer or investor will trust.
Websites built specifically for labs and researchers — publications pulled correctly, research framed credibly.
Every entry here is independently verifiable — not portfolio copy.
Three open-source packages, 7,000+ combined downloads — three sole-author preprints — one live example of the website module.
A Python package that resolves gene identifiers across naming conventions and databases, cutting out one of the most common friction points in cross-dataset analysis.
View on PyPI →A tool for working with Phred quality scores in sequencing data, built to speed up a routine but essential step of NGS quality control.
View on PyPI →A package for evolutionary motif analysis, used to identify and compare conserved sequence patterns across genomic datasets.
View on PyPI →Sole-author analysis integrating multiple omics layers within the TCGA breast cancer cohort to characterize patterns across the dataset.
Read preprint →A multi-omics investigation into MEF2C haploinsufficiency, examining its molecular signatures independently, sole-author, start to finish.
Read preprint →Whole-genome sequencing analysis of the HCC1395 reference cell line, characterizing somatic variation with a fully reproducible pipeline.
Read preprint →A demonstration build of the Module 3 offering: auto-synced publications feed, clean research-interest framing, no generic template filler.
View demo →No account managers, no subcontracted analysts. When you work with Cortessa, you work directly with the person who runs the analysis.
Cortessa is run by a single computational biologist — trained at METU, currently working in a biotech startup on T-cell isolation and computational antibody/nanobody design, and about to start an M.Sc. at TUM in Agricultural Biosciences.
The analysis work isn't theoretical. It's the same kind of work behind three sole-author preprints — spanning TCGA-BRCA multi-omics, MEF2C haploinsufficiency, and somatic whole-genome sequencing — and three open-source packages with a combined 7,000+ downloads, built and maintained independently.
That's the honest pitch: not a team, not an agency — one person with a public, checkable track record, taking on a small number of projects at a time so each one gets real attention.
Fixed scope, fixed price, confirmed before any work begins — no open-ended hourly billing.
Exact price depends on dataset size and analysis type — confirmed in writing before work starts. Larger or multi-dataset projects get a custom quote.
No open-ended hours. You know the scope and the price before we start.
Send the dataset and the question you're trying to answer — no need to pre-clean it.
A flat price for a defined deliverable, confirmed before any work begins.
QC, analysis, and publication-ready visuals delivered within about a week.
A written interpretation so the result is usable, not just technically correct.
Cortessa is deliberately narrow. That's not a limitation — it's the point.
Just tell us upfront — most academic clients pay via a lab purchase order or invoice rather than a personal card. We'll confirm your institution's process before quoting, and issue a formal invoice that fits it. If your university's PO process takes a few weeks, we'll plan the timeline around that rather than assuming a same-week start.
Yes. QC and preprocessing are part of the Analysis Starter Package, not a prerequisite for it. Send the data as it exists — raw, messy, partially labeled — and the cleanup happens as step one, not something you need to solve before reaching out.
Yes, happily, especially for unpublished data or pre-patent work. It's normal to ask, and we'll sign before any dataset changes hands if you'd like one in place.
Most commonly RNA-seq and other NGS data (FASTQ, BAM, count matrices), along with standard tabular formats (CSV, TSV, Excel) for other omics or experimental data. If you're not sure your format is supported, ask — it's a five-minute answer either way.
That happens, and it's not a failure — it's often the actual finding. The written summary will say so plainly, and one round of clarifying revisions is included if you need the analysis extended or re-framed around a follow-up question.
No — this is a paid service, not a collaboration seeking authorship. If your contribution standards call for acknowledgment given the scope of analytical work involved, that's entirely your call to make.
Yes — all work is remote, and most communication happens over email or a short call. Time zones are rarely an issue given the project turnaround is measured in days, not hours.
Then you'll be told that directly, ideally before any money changes hands. Generic web design, marketing work, and open-ended consulting are explicitly outside scope — see the section above — and it's more useful to say so early than to take on a project outside real expertise.
Tell us what you're working with — we'll tell you honestly whether we're the right fit.