Udemy - Synthetic Biology Mastery - 100 Labs with Nextflow
Synthetic Biology Mastery: 100 Labs with Nextflow
https://WebToolTip.com
Published 8/2026
Created by Dar Al Taqniya
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 112 Lectures ( 9h 37m ) | Size: 1.1 GB
From isolated scripts to production-grade synthetic biology platforms using Python, Nextflow, Docker & Kubernetes.
What you'll learn
⚡ Architect production-grade synthetic biology workflows using modern open-source engineering practices.
⚡ Build robust Python applications for sequence analysis, genomic data processing, and biological automation.
⚡ Design, simulate, and validate genetic circuits using computational models and engineering principles.
⚡ Develop scalable bioinformatics pipelines with Nextflow, Docker, Conda, and containerized execution.
⚡ Integrate Laboratory Information Management Systems (LIMS), APIs, audit trails, and automated laboratory workflows.
⚡ Engineer metabolic models, perform Flux Balance Analysis (FBA), and optimize biological production pathways.
⚡ Apply machine learning techniques to protein engineering, sequence prediction, and structural biology.
⚡ Implement enterprise biosecurity controls including sequence screening, encryption, RBAC, compliance automation, and governance.
⚡ Deploy secure cloud-native synthetic biology platforms on Kubernetes with monitoring, logging, disaster recovery, and infrastructure as code.
⚡ Complete an end-to-end sovereign synthetic biology platform that combines computational biology, workflow orchestration, security, observability, and production
Requirements
❗ You should have
❗ 1. Basic computer skills
❗ 2. Curiosity about biology, biotechnology, or software engineering
❗ 3. Basic Python knowledge is helpful but not required (Python fundamentals are explained throughout the labs)
❗ 4. No previous synthetic biology experience required
❗ Recommended Hardware
❗ 1. 8 GB RAM minimum
❗ 2. 16 GB RAM recommended
❗ 3. Stable internet connection for downloading open-source tools
❗ 4. Multi-core CPU
❗ Software you'll install during the course
❗ 1. Python 3.12+
❗ 2. Visual Studio Code
❗ 3. Docker Desktop or Docker Engine
❗ 4. Terraform
❗ 5. Kubernetes (Kind or Minikube)
❗ 6. Prometheus & Grafana