Tutorials, guides, and insights for researchers running bioinformatics without the command line.
A practical guide for wet-lab biologists who generate RNA-seq data but lack computational skills. Learn how AI-powered platforms let you run the entire pipeline by describing your experiment in plain English.
A practical guide for wet-lab biologists, structural biologists, and biochemists who need protein structures but don't have GPU infrastructure or computational expertise.
A practical guide for wet-lab researchers generating whole genome sequencing data who need to identify genetic variants but lack command-line bioinformatics skills.
A practical guide for wet-lab researchers performing ChIP-seq experiments who need to analyze their data but lack computational bioinformatics experience.
A practical guide for wet-lab researchers who want to analyze microbiome data — 16S amplicon or shotgun metagenomics — without writing a single line of code.
A practical guide for wet-lab researchers who want to analyze 10x Genomics single-cell RNA-seq data — from raw reads to cell type clusters — without writing Python or R.
Galaxy is open-source, but running it isn't free. We break down the real costs of self-hosting Galaxy — compute, storage, sysadmin labor, and opportunity cost — and compare it to a managed alternative.
Run Nextflow and Snakemake bioinformatics pipelines in the cloud without configuring AWS, writing Groovy, or managing infrastructure. A practical guide for wet-lab researchers.
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