Designed by researchers from the New York City-based Icahn School of Medicine at Mount Sinai and Princeton University in New Jersey, ImmuNet capitalizes on the availability of a plethora of patient information and combines computing power, models and algorithms to pull patterns and trends from large databases that would have previously been unrecognized.
“This new tool unlocks the insight contained in big data, the world’s biomedical research output, to help understand immunological mechanisms and diseases,” Stuart Sealfon, MD, chairman and professor in the department of neurology at Mount Sinai Health System and co-senior author of the publication, said in a statement. “The goal of ‘ImmuNet’ is to accelerate the understanding of immune pathways and genes, ultimately leading to the development of improved treatment for diseases with an immunological component.”
The tool enables researchers without specialized computational training to take advantage of machine learning and statistical analysis to glean new discoveries from the trove of public data, ultimately advancing the scientific understanding of the immune system and its role in disease and infection.
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