Case study

How the Allen Institute builds and shares computational pipelines for open neuroscience

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About the Allen Institute (AIND)

The Allen Institute is a Seattle-based independent nonprofit bioscience and medical research institute founded by Microsoft co-founder and philanthropist Paul G. Allen. It conducts large-scale research through foundational science to fuel the discovery and acceleration of new treatments and cures for diseases such as Alzheimer’s disease, heart disease, cancer, addiction, and more. The Allen Institute is committed to open science; one of its core values is to make all data and resources publicly available for external researchers and institutions to access and use.

The Challenge

The Allen Institute for Neural Dynamics (AIND) has a strong commitment to Open Science and wanted to share its pipelines with the wider neuroscience community.

Needed custom code

The AIND team had been running custom pipeline management code with on-prem HPCs.

Couldn't export

This system wasn’t designed for export or sharing outside of AIND.

Required support

This work needed significant support from a team of engineers working alongside the team.

Designed & built scalable pipelines with visual pipeline builder. Nextflow auto-generated, runs on AWS Batch.

Automated pipeline execution with the Code Ocean API, triggering when certain conditions are met.

Used the Pipeline export function to share their pipelines with the wider neuroscience community.

The team built, automated, and exported their Pipelines with Code Ocean:

The Results

Productivity

Pipeline build time went from 12 weeks to 3, a 4X speed increase.

Open science

Complete, interoperable pipelines now shareable with a single click.

Efficiency

10 AIND engineers successfully reallocated to higher impact work.

Self-service

Has allowed individual scientists to build pipelines with little support.

“Code Ocean makes it easy for our scientists to do their work reproducibly … new users to the platform can get far with just a little support; this gives our engineers time to focus on domain-specific challenges.”