Naouel Eldjouher

Naouel Eldjouher

Full-Stack Bioinformatician

I specialize in plant and bacterial genomics, bridging high-throughput wet-lab insights with containerized, cloud-native infrastructure and Nextflow.

LinkedIn · Github · Medium Medium · · Bluesky · @GroundUpBioinformatics

🧬 OmniDomain Build Logs
These are my notes during the building process.
Post 8: First route end to end: FastAPI, JWT auth, and the service layer Jun 14, 2026
Data layer done. Next: the FastAPI application, authentication, and the first real routes.
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Post 7: Building the data layer: session, models, repository Jun 12, 2026
This week I built the database layer for OmniDomain's FastAPI backend. Three files, each with one job. Moving from direct SQL in Streamlit to a production-grade session, ORM, and repository architecture.
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Post 6: Adding a FastAPI layer to OmniDomain Jun 10, 2026
The original project had Streamlit talking directly to PostgreSQL and AWS Batch. That was a deliberate choice. I wanted to focus on the pipeline infrastructure.
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Post 5: PhytoFlow Case 3 — Nuclear + Reference Jun 02, 2026
Same data, one extra flag: --reference. The pipeline switched from Helixer to BRAKER3 automatically. 770 proteins vs 527 — a 46% increase from protein evidence alone.
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Post 4: PhytoFlow Nuclear Pipeline — First Full Run May 29, 2026
With the organelle case validated, PhytoFlow moved to its first nuclear genome run. The goal was not a publishable genome, it was a pipeline validation:
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Post 3: First HiFi Assembly, a Complete Chloroplast May 23, 2026
OmniDomain now has three new pipelines under active development: PhytoFlow for plant genome assembly and annotation, FungalFlow for fungal genome assembly and biosynthetic gene cluster discovery, and MetaCflow for bacterial shotgun metagenomics and MAG recovery.
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Post 2: Designing the Nextflow Repository Structure May 22, 2026
Three pipelines. One repo. The structure determines everything. Each pipeline gets its own main.nf and modules.config. One global nextflow.config handles profiles, resource limits and shared params.
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Post 1: The OmniDomain Blueprint May 20, 2026
After finishing NextAMR, I'm expanding to fungi and plants. OmniDomain is a unified Nextflow + AWS Batch platform for bacterial, fungal, and plant genomics — one shared infrastructure, three pipeline engines.
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💻 Projects
Current Project

🌐 OmniDomain — Multi-Kingdom Cloud Genomics Platform

Nextflow DSL2 | AWS Batch | Amazon S3 | Docker | Terraform | Streamlit
  • Unified Infrastructure: One shared AWS Batch setup, Terraform, and Streamlit UI powering three pipeline engines — NextAMR, FungalFlow, and PhytoFlow.
  • Multi-Kingdom: Bacterial WGS & AMR detection, fungal genome assembly & BGC discovery, and HiFi-first plant genome assembly from a single codebase.
  • Validated: Assembled a complete Arabidopsis chloroplast — 155,667 bp, 0 gaps, 100.8% expected size — from 12,745 PacBio HiFi reads.
  • BYOC Model: All compute runs in your AWS account. The platform provides the pipelines and infrastructure code — you own the compute.
  • 🐙 Code: Explore the OmniDomain Repository on GitHub

🦠 NextAMR (AMR-Flow) — Cloud-Native Bacterial Genome Assembly & AMR Profiling

Nextflow DSL2 | AWS Batch | Amazon S3 | Docker | Terraform | Streamlit
  • Automated Cloud Infrastructure: Provisioned an event-driven AWS architecture using Terraform (IaC) to handle automated job submission via AWS Batch.
  • Cost Efficiency & Portability:Dual-queue AWS Batch strategy — EC2 Spot for short-lived jobs (60–80% cost savings), On-Demand EC2 for long-running assemblers to prevent mid-assembly Spot interruptions. Fully containerized with Docker for cross-platform reproducibility.
  • 🐙 Code & Architecture: Explore the NextAMR Repository on GitHub
  • 📖 Read on Medium: From Terminal Scripts to the Cloud

🎓 Baktflow — Automated Bacterial Genome Analysis Pipeline

M.Sc. Thesis Project | Nextflow | Genome Assembly & Functional Annotation
  • Reproducible Workflows: Built an end-to-end bacterial genomics workflow to automate quality control, short/long-read hybrid assembly, and downstream annotation.
  • Academic Foundations: Developed as the core software deliverable for my M.Sc. thesis at Justus Liebig University Giessen. (Record: Zenodo 10.5281/zenodo.14995561)

🛠️ Tools & Technologies I Work With