Zak Kohane
Isaac Samuel Kohane, MD, PhD
Chair of the Department of Biomedical Informatics, Harvard Medical School
Marion V. Nelson Professor of Biomedical Informatics, Harvard Medical School
10 Shattuck Street, Boston, MA 02115

Over the last 30 years, the research agenda of Isaac Kohane  has been driven by the vision of what biomedical researchers could do to find new cures, provide new diagnoses and deliver the best care available if data could be converted more rapidly to knowledge and knowledge to practice. In so doing, Kohane has designed and led multiple internationally adopted efforts to “instrument” the healthcare enterprise for discovery and to enable innovative decision-making tools to be applied to the point of care. At the same time, the new insights afforded by ’omic-scale molecular analyses have inspired him and his collaborators to work on re-characterizing and reclassifying diseases such as autism, rheumatoid arthritis and cancers. In many of these studies, the developmental trajectories of thousands of genes have been a powerful tool in unraveling complex diseases. Kohane currently leads three NIH-funded projects that cut across the entire agenda:

  1. A Center for Excellence in Genomic Science to study neuropsychiatric disease at multiple levels (from molecular characterization of induced neurons obtained from fibroblasts of patients to automated classification of the textual component of their electronic medical record).
  2. The Coordinating Center for the Undiagnosed Diseases Network. Where patients with rare and unknown diseases are provided with combined clinical and molecular diagnoses in a nationally-scaled infrastructure so that they can see the right expert with all their relevant data at hand.
  3. Center for Excellence in Big Data to Knowledge to both create a nationally scaleable research data-sharing infrastructure and demonstrate its use for neurodevelopmental diseases.

Kohane is always on the look out for like-minded “quants” who share the same goals to bring a better future for medicine and biomedical science to the present.

DBMI Research Areas
DBMI Courses
Current Postdoctoral Fellowship Opportunities
Machine Learning in Medicine. Reply.
Authors: Rajkomar A, Dean J, Kohane I.
N Engl J Med
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Suicide Rates Among Adolescents and Young Adults in the United States, 2000-2017.
Authors: Miron O, Yu KH, Wilf-Miron R, Kohane IS.
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Batch correction evaluation framework using a-priori gene-gene associations: applied to the GTEx dataset.
Authors: Somekh J, Shen-Orr SS, Kohane IS.
BMC Bioinformatics
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Evaluation of the association of bariatric surgery with subsequent depression.
Authors: Yuan W, Yu KH, Palmer N, Stanford FC, Kohane I.
Int J Obes (Lond)
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Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction.
Authors: Chen ML, Doddi A, Royer J, Freschi L, Schito M, Ezewudo M, Kohane IS, Beam A, Farhat M.
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Deep Learning Benchmarks on L1000 Gene Expression Data.
Authors: McDermott M, Wang J, Zhao WN, Sheridan SD, Szolovits P, Kohane I, Haggarty SJ, Perlis RH.
IEEE/ACM Trans Comput Biol Bioinform
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Machine Learning in Medicine.
Authors: Rajkomar A, Dean J, Kohane I.
N Engl J Med
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Adversarial attacks on medical machine learning.
Authors: Finlayson SG, Bowers JD, Ito J, Zittrain JL, Beam AL, Kohane IS.
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Pre-existing autoimmune disease and the risk of immune-related adverse events among patients receiving checkpoint inhibitors for cancer.
Authors: Kehl KL, Yang S, Awad MM, Palmer N, Kohane IS, Schrag D.
Cancer Immunol Immunother
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f(1Feature Extraction for Phenotyping from Semantic and Knowledge Resources.
Authors: Ning W, Chan S, Beam A, Yu M, Geva A, Liao K, Mullen M, Mandl KD, Kohane I, Cai T, Yu S.
J Biomed Inform
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