💻 Software & Environment Setup
Bioinformatics & Computational Biology
The computational toolchain and environment used throughout AI and Machine Learning in Crop Genomics.
Machine learning crop genomics courseMachine learning crop genomics online trainingBest machine learning crop genomics certificationMachine learning crop genomics for researchersMachine learning crop genomics hands-on workshopLearn machine learning crop genomics
# Recommended conda environmentconda create -n dstc_env python=3.11 -yconda activate dstc_envpip install biopython pandas pysam scikit-bioBiopython
Sequence I/O, BLAST parsing, phylogenetics
Sequence I/O, BLAST parsing, phylogenetics
SAMtools / BCFtools
Alignment & variant file manipulation
Alignment & variant file manipulation
Bioconductor (R)
DESeq2, edgeR & limma for expression analysis
DESeq2, edgeR & limma for expression analysis
Nextflow
Reproducible, portable NGS pipelines
Reproducible, portable NGS pipelines
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 AI and Machine Learning in Crop Genomics
e-Certificate and e-Marksheet issued on successful completion.
