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Credit: Nature Biotechnology
Tel Aviv — June 18, 2018 — New data published in Nature Biotechnology, represents the largest ever analysis of immune cell signaling research, mapping more than 3,000 previously unlisted cellular interactions, and yielding the first ever immune-centric modular classification of diseases. These data serve to rewrite the reference book on immune-focused inter-cellular communications and disease relationships.
The immune system is highly complex and dynamic, and with a new immunology paper published every 30 minutes, there is no practical way for a human to grapple with the sheer size and diversity of the field. As this body of data grows, machine learning methods will be the only practical way of fully leveraging all the efforts being made to advance immunology and science in general.
Standardizing and contextualising the full body of cell-cytokine relationships is vital in our ability to broaden immune system understanding. Based on this curated knowledge base, 355 hypotheses for entirely novel cell-cytokine interactions were generated through the application of validated prediction technologies.
These alone, represent discoveries born out of a better contextual understanding of existing immune system knowledge. This potential becomes even more powerful
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