Machine learning (ML) is used for multiple healthcare and life sciences (HCLS) applications, including medical imaging, protein folding, drug discovery, and gene editing. While Nextflow pipelines (like those in nf-core) are commonly used for genomics, they are also being adopted for machine learning workloads.

In this artice, we explain how to build an example Nextflow pipeline that performs ML model-training and inference for image analysis, illustrating how Nextflow supports custom ML-based workflows. We also discuss how health care and life science customers are using this today.

In part ii, we’ll provide a step-by-step guide explaining how users new to the Seqera Platform can rapidly get started with AWS