Official landing page for OmniBioAI Studio — an AI-native, reproducible bioinformatics platform for multi-omics research and workflow automation.
🌐 Live site: omnibioai.org
📺 Demo: Watch on YouTube
This repository contains the static HTML/CSS/JS landing page for OmniBioAI Studio. The site is a single-page application with multiple sections covering features, supported omics modalities, system requirements, platform downloads, architecture, publications, and a private beta access request form.
The site is built with vanilla HTML, CSS, and JavaScript — no build tools or frameworks required.
| File | Description |
|---|---|
index.html |
Main landing page (hero, features, omics, downloads, architecture, publications, beta form) |
about.html |
About page |
admin.html |
Beta access admin panel |
The download section provides installers for:
macOS
- Apple Silicon (ARM64) — DMG · 101 MB
- Intel (x86_64) — DMG · 105 MB
Linux x86_64
- AppImage (any distro, Ubuntu 20.04+)
- DEB package (Ubuntu / Debian / Mint)
- RPM package (RHEL / Fedora / CentOS)
Linux ARM64 (NVIDIA DGX / AWS Graviton / Raspberry Pi)
- AppImage ARM64
- DEB ARM64
- RPM ARM64
Windows
- Windows installer (NSIS EXE) — ~90 MB
All installers include a 30-day free trial license. Access is gated behind a beta approval form.
The landing page combines repository-specific catalog figures. They are not interchangeable counts: TES reports configured tool definitions, Workbench reports enabled plugins, and container availability varies by deployment.
| Metric | Value |
|---|---|
| Studio catalog tools | 12,110+ |
| TES tool definitions | 15,012 |
| Workbench plugins | 351 |
| Container inventory | Historical 1,120+ baseline; deployment-dependent |
| Workflow bundles | 600+ |
| Agentic pipelines | 10+ |
| Knowledge domains | 150+ |
| Microservices | 40 services in the current Studio Compose stack |
The Studio download links on this page currently target the private-beta
v0.7.0-beta artifacts. A stable v0.7.0 release also exists in the Studio
repository; update the links and version labels together when switching the
landing page to stable distribution.
| Component | Minimum | Recommended |
|---|---|---|
| RAM | 16 GB | 32 GB (64 GB with local LLM) |
| Storage | ~5 GB (Docker images) + 50–200 GB data | — |
| OS | Ubuntu 20.04+, macOS 12+, Windows 10/11 (WSL2) | — |
| Docker | Engine 24+ or Docker Desktop | — |
| GPU | Optional (NVIDIA + nvidia-container-toolkit for local LLM) | — |
Fully offline after first boot. Internet required only for initial Docker image pull (~10 GB from ghcr.io).
- Single-cell transcriptomics (scRNA-seq)
- Whole exome & genome sequencing (WGS / WES)
- Proteomics & mass spectrometry
- ATAC-seq (chromatin accessibility)
- ChIP-seq (protein-DNA interactions)
- Bulk RNA-seq
- Spatial transcriptomics
- Spatial + single-cell integration
- Structural variant (SV) calling
- DNA methylation / bisulfite sequencing
- Circular RNA (circRNA)
- Multi-omics integration
- CRISPR screen analysis
- Variant prioritization ML
- Drug discovery / GNN-based target identification
- Clinical translational pipelines
Languages & Frameworks
Python · R · JavaScript · FastAPI · Django · React
Workflow Engines
Nextflow · WDL · Snakemake · CWL
Bioinformatics Tools
GATK · Seurat · DESeq2
AI / ML
LangGraph · PyTorch · CUDA · HuggingFace · Ollama
Infrastructure
Docker · Kubernetes · Slurm · AWS · Azure · GCP
Data & Messaging
MySQL · Redis · Celery
OmniBioAI Studio UI (Desktop Frontend)
│ Service handshake & orchestration
Agentic AI Orchestration (LangGraph / Ollama / HuggingFace)
│ Orchestration & Data Mapping
BioFlow Runtime Engine (Nextflow / WDL / Snakemake)
│ Tracking & Provenance Link
LIMS-X Metadata & Sample Tracking System
│ Infrastructure Layer
GPU Accelerated Stack (CUDA / NVIDIA DGX Spark)
Selected peer-reviewed work powered by OmniBioAI platform methods:
- 2025 — Genetic mutations in lymphocytic variant of hypereosinophilic syndrome: study of five siblings — Frontiers in Medicine
- 2018 — Whole Exome Sequencing identifies common and rare variant Metabolic QTLs in a Middle Eastern Population — Nature Communications
- 2015 — MetaRNA-Seq: An Interactive Tool to Browse and Annotate Metadata from RNA-Seq Studies — BioMed Research International
OmniBioAI Studio v0.7.0-beta is in private beta. Researchers can apply via the request form on the landing page. Approved researchers receive a platform-specific download link and onboarding support within 1–2 business days.
This is a static site — no build step required.
# Clone the repo
git clone https://github.com/OmniBioAI/omnibioai-landing.git
cd omnibioai-landing
# Serve locally (any static server)
python3 -m http.server 8080
# or
npx serve .Then open http://localhost:8080 in your browser.
| Repo | Description |
|---|---|
| omnibioai-studio | Desktop application (Electron) — releases and installers |
© 2026 OmniBioAI. All rights reserved.