Hundreds of millions of people suffer from autoimmune diseases, which include rheumatoid arthritis, diabetes, multiple sclerosis and Crohn’s Disease.
Many academic labs, biomedical research institutions, and pharmaceutical companies are working hard to better understand autoimmune disorders and infectious diseases that attack the immune system.
Five to six years ago, researchers were able to sequence hundreds of immune-system molecules (like antibodies) in the human body. Today they can sequence tens of millions.
These data are making the human immune system less of a black box as they reveal the construction of the immune system along with the how, why, and when our body responds to various diseases.
This is critical for studying autoimmune diseases and developing medical techniques that augment or use our immune system, such as vaccines, therapeutic antibodies, and cancer immunotherapies, to name a few.
However, storing, organizing, and analyzing these data has become a rapidly escalating big-data challenge.
To facilitate this study of immunogenetics, researchers at Simon Fraser University in Vancouver, Canada have created a Research Software Platform called iReceptor. A secure, distributed database, this tool enables researchers to share and analyze huge datasets via National Research and Education Networks.
What makes this tool particularly exciting is its ability to include metadata (such as gender, ethnicity, treatment, and outcome), allowing researchers to understand which conditions activate or suppress various immune system genes.
Because iReceptor pools scarce data in a secure way, research from multiple angles of a specific condition can illuminate immune system failures, pointing to clinical treatments for rare conditions as well as commonly occurring diseases.
And that opens up a whole new era of better treatments and even cures for the 80+ autoimmune diseases known to us.
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