💻 Software & Environment Setup
Biotechnology & Genetic Engineering
The computational toolchain and environment used throughout Lab-on-a-Chip: Miniaturized Genetic Engineering Course.
Learn lab chip miniaturizedLab-on-a-chip training for researchersMiniaturized training for researchersGenetic training for researchersLab chip miniaturized hands-on trainingLab chip miniaturized for PhD students
# Recommended conda environmentconda create -n dstc_env python=3.11 -yconda activate dstc_envpip install biopython pandas dna-features-viewerBenchling / SnapGene
Cloning design & plasmid maps
Cloning design & plasmid maps
CRISPOR
Guide-RNA design & off-target scoring
Guide-RNA design & off-target scoring
Primer3
PCR primer design
PCR primer design
Galaxy
No-code reproducible bioinformatics
No-code reproducible bioinformatics
Supported OS: Linux (Ubuntu 22.04+), macOS, or Windows via WSL2.
Hardware: 16 GB RAM minimum; a CUDA GPU helps for deep-learning modules.
Earn government-registered certification in Lab-on-a-Chip: Miniaturized Genetic Engineering Course
e-Certificate and e-Marksheet issued on successful completion.
