AWS Life Sciences Archive

Bioinformatics Pipeline Automation and Optimization via AWS and PTP

In this presentation, Scott Scheirey, Scientific Partner Advisor at PTP, addresses common challenges faced by computational biologists in optimizing bioinformatics workflows. He highlights the use of AWS Batch, Nextflow, and Airflow to enhance pipeline efficiency, reliability, and speed. Scheirey explains how these tools can help process large volumes of genomic data more quickly and cost-effectively, ultimately supporting research validation and clinical trials.

Infrastructure as Code on AWS For Accelerating Science

View PTP’s case study on implementing Infrastructure as Code (IaC) solutions for a life sciences startup. The focus is on creating a scalable, automated, and secure data processing environment using AWS services and tools such as EC2, Lambda, and Terraform. The goal is to streamline research validation, optimize costs, and ensure data security.

When to Use AirFlow vs NextFlow for Pipelines

Explore the advantages and practical scenarios for using Apache AirFlow and NextFlow for data pipelines. This article delves into how AirFlow excels in managing complex workflows, orchestrating ETL jobs, and supporting machine learning data preparation on AWS, while also highlighting the capabilities of NextFlow for scientific workflows.