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A study from Cornell researchers could enable a quantum leap forward in identifying and deciphering cancer-driving genetic mutations, the first step in developing effective therapeutics.

A tool co-developed by Cornell researchers uses AI and machine learning to solve and predict how human proteins might interface and interact with other proteins, which can greatly accelerate fundamental research and clinical precision medicine.

A new study testing the accuracy of existing methods used to predict the genetic variation that cause infertility found that relying on computational or in vitro experiments alone is insufficient.

A computational tool will greatly benefit our understanding of the SARS-COV-2 virus and the development of drugs that block sites where the virus binds with human proteins.

Seed grants and symposia based on themes from the Office of Academic Integration have bridged researchers from the Ithaca and New York campuses and have brought a high return on investment to Cornell.