Nicholas Tatonetti

Nicholas Tatonetti


Associate Professor of Biomedical Informatics (in Systems Biology and in Medicine)


Department of Systems Biology
Center for Computational Biology and Bioinformatics
Department of Medicine
Department of Biomedical Informatics
Center for Cancer Systems Therapeutics


(212) 305-2055

Nicholas Tatonetti is an associate professor in the Department of Biomedical Informatics. He is developing methods for integrating and analyzing heterogeneous data types, including next-generation genome and transcriptome sequencing, metabolomics, proteomics, and electronic medical records. He and members of his laboratory develop algorithms and methods based on rigorous computational and mathematical approaches that can be used to account for the lack of controls within large, heterogenous data sets. The goals of his research are to understand basic biology, and ultimately to use this knowledge to improve human health.

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Nicholas Tatonetti, PhD: Always Thinking Outside the Box
Nicholas Tatonetti solves problems. He has always enjoyed it, and as the informatics community has discovered, he is both creative and proficient in his methods. Awarded tenure this year and promoted to associate professor, Dr. Tatonetti focuses on the use of advanced data science methods, including AI and machine learning, to investigate medicine safety. Learn more about Dr. Tatonetti and his innovative research in this recent faculty profile.
Newly Tenured Systems Biology Faculty
Congratulations to Drs. Yufeng Shen, Nicholas Tatonetti, and Chaolin Zhang of the Department of Systems Biology, who have been awarded tenure and promoted to associate professor. Their new appointments are effective July 1, 2019.
Columbia Highlights MD/PhD Student Research
Congratulations to Phyllis Thangaraj, an MD/PhD student in the Nicholas Tatonetti lab, for her winning poster session at an event recognizing aspiring physician-scientists from the Vagelos College of Physicians and Surgeons. Students in the MD/PhD program training program at Columbia University Irving Medical Center presented their research posters at the 14th annual Student Research Symposium on April 25, and topics included a wide range, such as Alzheimer’s disease, stroke, and stem cells. Thangaraj discussed ongoing research in applying machine learning methods to phenotype acute ischemic stroke patients in electronic health records.
Electronic Health Record Analysis Shows Which Diseases Run in Families
Findings from a new study by researchers at Columbia University Irving Medical Center and NewYork-Presbyterian could streamline efforts to understand and mitigate disease risk—especially for diseases with no known disease-associated genes. The study, published by Cell, was co-led by Systems Biology’s Nicholas Tatonetti, PhD, and David Vawdrey, PhD, of Biomedical Informatics.
From Code to Cure
The cover story of Columbia Magazine's Spring 2018 issue spotlights how Columbia University researchers, including Systems Biology faculty Andrea Califano, Dr, and Nicholas Tatonetti, PhD, are rewriting the rules of medical research in the age of data science. This new era also is providing opportunities to study the world in entirely new ways. Nowhere is this more evident than in medicine.