New Tool Shrinks Big Data in Biology Studies at SLAC's X-ray Laser

Inspired by 1970s method, Stanford scientists find a way to go back and improve past scientific results.

Written bySLAC National Accelerator Laboratory
| 4 min read
Register for free to listen to this article
Listen with Speechify
0:00
4:00

Understanding how our biology works at the atomic scale is a key to understanding and treating disease. But seeing the structure of proteins, the body’s microscopic machines, is a “big” problem: it requires big science facilities, generates big data – enough to fill tens of thousands of DVDs – and can require big research collaborations.

Now, a team led by Stanford scientists has created software that tackles the big data problem for X-ray laser experiments at the Department of Energy’s SLAC National Accelerator Laboratory. The program allows researchers to tease out more details while using far fewer samples and less data and time. It can also be used to breathe new life into old data by reanalyzing and improving results from past experiments at the Linac Coherent Light Source (LCLS) X-ray free-electron laser, a DOE Office of Science User Facility.

The tool, which will become publicly available, works by analyzing partial, X-ray-produced images of crystallized protein structures, known as diffraction patterns, that might otherwise be discarded and comparing them with known data to fill in the blanks and produce a more complete picture of these biomolecules. When applied to a whole set of data, this can reveal new structural details.

To continue reading this article, sign up for FREE to
Lab Manager Logo
Membership is FREE and provides you with instant access to eNewsletters, digital publications, article archives, and more.

CURRENT ISSUE - October 2025

Turning Safety Principles Into Daily Practice

Move Beyond Policies to Build a Lab Culture Where Safety is Second Nature

Lab Manager October 2025 Cover Image