Reference Material Proposal for Multiomic Data Reproducibility in Artificial Intelligence

Serdar HocamAuthor & Editor

A new article published in Nature Biotechnology discusses the use of common calibrators in multiomic measurements to ensure the reliability of artificial intelligence tools.

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Ensuring multiomics data reproducibility for artificial intelligence with reference materials as a common calibrator - Nature Biotechnology

An article published in Nature Biotechnology emphasized that reference materials should be adopted as common calibrators to ensure multiomic data reproducibility for AI-powered tools.

Key findings and recommendations of the article

In the study authored by Leming Shi and colleagues, it was stated that common calibrators are essential for multiomic measurements to be reliable and consistent.

According to the proposed method, it is of great importance that reference materials are profiled simultaneously with the test samples.

Ratio-based reporting for artificial intelligence tools

It is recommended that the obtained multiomic results be reported in the form of sample-to-reference ratios in order to be fully compatible with artificial intelligence applications.

Through this reporting format, achieving a higher level of standardization across different laboratories and datasets is targeted.