Inferring the underlying ecological networks of microbial communities is important to understanding their structure and responses to external stimuli. But it can be very challenging to make accurate network inferences. In a paper published in Nature Communications, researchers at Brigham and Women’s Hospital detail a method to make the network inference easier by utilizing steady-state data without altering microbial communities.