Bioinformatics is done with code. Two languages dominate the field: Python for general-purpose scripting and sequence work, and R for statistics and the analysis of genomic data. This module gives you a first look at both, so you can start working with real biological data.
You'll start with Python and Biopython, a library built for biologists. You'll see how to read FASTA and FASTQ files, handle sequences, work with NCBI databases, and run simple analyses such as GC content. These are the formats and databases you met in the previous module, now handled in code.
Then you'll move to R, starting with the basics and then Bioconductor, the collection of R packages for genomic data. You'll use R heavily in later modules such as RNA-seq. Once you've finished, move on to Command Line & Linux.
A hands-on introduction to Biopython. Covers reading FASTA and FASTQ files with SeqIO, GC content, transcription and translation, NCBI Entrez, pairwise alignment, and BLAST.
A beginner-friendly introduction to R for people working with biological data.
The first session of a series on using R for bioinformatics, covering why R is widely used for biological data analysis.