Interactions-based classification of a single microbial sample

Yogev Yonatan, Shaya Kahn, Amir Bashan

Research output: Contribution to journalArticlepeer-review


To address the limitation of overlooking crucial ecological interactions due to relying on single time point samples, we developed a computational approach that analyzes individual samples based on the interspecific microbial relationships. We verify, using both numerical simulations as well as real and shuffled microbial profiles from the human oral cavity, that the method can classify single samples based on their interspecific interactions. By analyzing the gut microbiome of people with autistic spectrum disorder, we found that our interaction-based method can improve the classification of individual subjects based on a single microbial sample. These results demonstrate that the underlying ecological interactions can be practically utilized to facilitate microbiome-based diagnosis and precision medicine.

Original languageEnglish
Article number100775
JournalCell Reports Methods
Issue number5
StatePublished - 20 May 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors


  • CP: Systems biology
  • dissimilarity-overlap analysis
  • microbial dynamics
  • microbial ecosystems
  • microbial networks
  • microbial samples classification
  • microbiome-based diagnosis
  • precision medicine


Dive into the research topics of 'Interactions-based classification of a single microbial sample'. Together they form a unique fingerprint.

Cite this