Notebooks
A pre-configured analysis environment where scientists explore results, generate code, and turn discoveries into team standards. No setup. BioMind built in.
The Problem
The barrier to insight shouldn't be knowing Python.
Great pipelines produce data. The real insight comes from exploration, and exploration is gated by programming expertise most scientists don't have.
Code is the gatekeeper
Most researchers aren't bioinformaticians. Insights stop at the output file because turning results into figures requires programming expertise most scientists simply don't have.
Exploration is manual and slow
Downloading outputs, spinning up local environments, installing conflicting dependencies, and writing one-off scripts that break the moment something changes.
Nothing gets reused
Every analysis is bespoke. The next project starts from scratch. The logic from last quarter's discovery is buried in a notebook nobody else can run.
How It Works
From exploration to standard
in four steps
From blank notebook to reproducible team workflow in four steps. Your environment is ready. BioMind is built in.
Step 01
Your Sarek run just finished. Click once and the results are already inside a Notebook: VCF, count matrix, MultiQC report. No downloading, no re-uploading, no environment setup.
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Step 01: Create a Notebook
Start from scratch or fork an existing one. Your environment is pre-configured with the scientific stack, pandas, numpy, matplotlib, ggplot2, samtools, bedtools, and more. No setup, no version conflicts.
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Step 02: Code or Describe
Write Python or R directly, or describe what you need in plain English. BioMind generates executable, analysis-ready code inside your notebook and explains every step.
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Step 03: Run and Explore
Execute cells, adjust thresholds, and visualize findings. Bring in pipeline outputs directly or pull public data from GEO, SRA, or IPG using an accession number.
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Step 04: Standardize and Share
Turn a successful analysis into a reusable multi-step workflow. Each step is independently adjustable, so your team can run the same logic across projects without starting from scratch.
The Environment
Built for science,
not infrastructure.
Everything a scientist needs is already in place. No installs, no dependency hell, no context-switching. The Notebook is where analysis actually happens.
Pre-Configured Environment
Every Notebook launches with the scientific Python and R stack ready. Pandas, NumPy, Matplotlib, ggplot2, Samtools, Bedtools, and more. Install additional packages via pip at any time. Access pipeline outputs directly without downloading or re-uploading files.
Public Dataset Integration
Bring in data from GEO, SRA, and IPG by providing an accession number. The data is fetched directly into your Notebook file system, ready for validation, benchmarking, or exploratory comparison with your own datasets.
Multi-Step Analysis
Structure exploratory work into modular, reusable steps. Each step is independently adjustable without rerunning the entire workflow. Turn a successful session into a team standard, any collaborator can run the same logic with their own parameters.
AI Inside the Notebook
Your AI research partner.
Inside every notebook.
BioMind is the AI agent built into every Notebook. It sees your cells, your outputs, and your data. It responds to what is actually happening in your analysis.
BioMind
AI Write in plain English.
Get executable code.
Many researchers face a frustrating gap: biological insights locked behind bioinformatics pipelines that require coding expertise most scientists don't have. BioMind bridges that gap. Describe your goals in plain language, and it generates executable Python or R directly inside your notebook, debugs what breaks, and explains every step.
Code Generation
Generate analysis-ready code in Python or R from plain English descriptions.
Error Debugging
Read error logs, explain what went wrong, and suggest fixes in plain language.
Visualization
Create PCA plots, heatmaps, and interactive figures from your data without writing boilerplate.
Tool Recommendations
Recommend the right libraries and approaches for your data type and research question.
Result Interpretation
Summarize outputs, flag anomalies, and explain what your results mean in context.
Parameter Guidance
Recommends appropriate thresholds and analysis parameters based on your data type and research goal.
Public Data Access
Fetch datasets from GEO, SRA, or IPG by accession number directly into your notebook file system.
Conversational Memory
Remembers your analysis context across Notebooks so follow-up questions build on previous steps.
Not a Generic Chatbot
Unlike ChatGPT or Copilot, BioMind sits directly inside your workflow with live access to your notebook cells, pipeline outputs, error logs, and data. It responds to what is actually happening in your analysis, not a description of it. It thinks in terms of your research objective and your data type, not code completion.
Why Pan.bio Notebooks
What makes Pan.bio Notebooks
different.
Exploration Without Friction
Walk through any analysis interactively. No restrictions on what you run, no environment setup, no version conflicts. The full scientific stack is ready when you are.
An AI That Sees Your Work
BioMind has live access to your notebook cells, pipeline outputs, and error logs. It responds to what is actually happening in your analysis, not a description of it.
From Experiment to Standard
Multi-step analysis turns one-off discoveries into reproducible workflows your whole team can run, reducing the gap between exploration and production.
Built for Teams
Multiple users can work in the same Notebook simultaneously. Shared data, independent BioMind interactions, and full audit trails for every analysis.
Public Data, Zero Friction
GEO, SRA, and IPG are one accession number away. Benchmark against public datasets or explore new populations without leaving the platform.
Enforced at the infrastructure level, your data stays in your jurisdiction, always.
Your Research, Unblocked
Notebooks give scientists the freedom to explore without the friction of environment setup, and the structure to turn discoveries into reproducible team workflows. BioMind is built in.
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