Publications:41
Maria Suprun, PhD, MPH
About Me
Maria Suprun, PhD, is an Assistant Professor of Pediatrics in the Division of Allergy and Immunology in the Jack and Lucy Clark Department of Pediatrics at Mount Sinai and the Mount Sinai Kravis Children’s Hospital and in the Department of Population Health Science and Policy at the Icahn School of Medicine at Mount Sinai.
Dr. Suprun completed her PhD in Biomedical Sciences and masters in Biostatistics at the Icahn School of Medicine at Mount Sinai. Her research combines laboratory and machine learning techniques to understand how antigen and epitope-specific antibodies develop in allergy and in response to treatment.
Research Focus
Dr. Suprun’s research focus’ currently on Identification of disease biomarkers is an important step to personalized diagnostic and therapeutic approaches. Dr. Suprun develops assays and computational tools for the detection of epitope-specific antibodies, and in addition to IgE and IgG, studies epitope-specific IgM, IgD, and IgA. These antibody profiles are used to define allergic phenotypes and develop machine learning algorithms to not only improve allergy diagnostics but also track how patients respond to therapy.
Language
Position
About Me
Maria Suprun, PhD, is an Assistant Professor of Pediatrics in the Division of Allergy and Immunology in the Jack and Lucy Clark Department of Pediatrics at Mount Sinai and the Mount Sinai Kravis Children’s Hospital and in the Department of Population Health Science and Policy at the Icahn School of Medicine at Mount Sinai.
Dr. Suprun completed her PhD in Biomedical Sciences and masters in Biostatistics at the Icahn School of Medicine at Mount Sinai. Her research combines laboratory and machine learning techniques to understand how antigen and epitope-specific antibodies develop in allergy and in response to treatment.
Research Focus
Dr. Suprun’s research focus’ currently on Identification of disease biomarkers is an important step to personalized diagnostic and therapeutic approaches. Dr. Suprun develops assays and computational tools for the detection of epitope-specific antibodies, and in addition to IgE and IgG, studies epitope-specific IgM, IgD, and IgA. These antibody profiles are used to define allergic phenotypes and develop machine learning algorithms to not only improve allergy diagnostics but also track how patients respond to therapy.