Genomic Analysis for
Research Labs & Academia
Run reproducible pipelines, explore data interactively with AI, and turn exploratory analyses into reusable workflows your entire lab can standardize on.
The Challenge
The Problem for Research Labs
Most research labs rely on fragmented tools and custom scripts for genomic analysis. Each project ends up building its own setup. Workflows become difficult to maintain, compare, and repeat across teams. Results become hard to reproduce. Collaboration slows. And as datasets grow, the infrastructure buckles under its own weight.
How Pan.bio Helps
The capabilities behind the difference
Pan.bio gives research labs a structured analysis environment that balances automation with flexibility:
Validated nf-core pipelines
Run Sarek, RNA-seq, single-cell RNA-seq, Amplicon-seq, metagenomics, and more without writing code. Pipelines are versioned, reproducible, and ready out of the box.
Notebooks with BioMind
Drop into a Jupyter-style notebook with pre-installed bioinformatics libraries (pandas, numpy, matplotlib, ggplot2, samtools, bedtools, and more). Ask BioMind to write Python or R code for you in plain English, debug errors, or recommend the right library for your data.
Public datasets integrated
Fetch GEO, SRA, and IPG data directly by accession number, no downloading, no re-uploading. Validate your results against public benchmarks in minutes.
Multi-step reusable analyses
Turn a successful exploratory notebook into a reusable workflow your whole team can run with one click, using dropdowns and fields to adjust parameters without rewriting code.
Collaboration built in
Multiple users can work in the same Notebook on shared data. Each user gets their own BioMind chat history.
Real Workflow Example
A graduate student working on RNA-seq differential expression
-
Upload FASTQ files to Pan.bio
-
Run the nf-core RNA-seq pipeline through the UI, no config files, no command line
-
Pipeline outputs flow directly into a Notebook
-
Ask BioMind: "Generate a volcano plot of my differential expression results", get runnable Python code
-
Ask BioMind: "Explain why these genes have such high variance", get an interpretation in plain English
-
Save the workflow as a multi-step analysis so the rest of the lab can run it on their own samples
What You Gain
Real outcomes, not just features
Tangible results from teams that moved their genomic work onto Pan.bio.
-
Reproducibility by default.
Every pipeline runs the same way every time, with full version control.
-
Accessibility for non-coders.
Lab members without programming backgrounds can run analyses through the UI or describe them to BioMind.
-
Time back for actual science.
Less time debugging scripts, more time interpreting results.
-
One platform instead of five.
Pipelines, notebooks, datasets, and collaboration in one place.
Enforced at the infrastructure level, your data stays in your jurisdiction, always.
Ready to Transform Your Lab's Workflow?
Pan.bio gives your lab validated pipelines, AI-assisted notebooks, and reusable workflows, all in one platform.
No credit card required · Start in minutes