Mayte Suarez-Farinas, PhD Email Mayte Suarez-Farinas
- PROFESSOR | Population Health Science and Policy
- PROFESSOR | Genetics and Genomic Sciences
I have vast experience in clinical trials design and statistical techniques as well as data mining and bioinformatics techniques applied to high throughput data, including arrays, next generation sequencing data, metabolomics and proteomics. For the last 10 years, I have been working in the interface of biomedical research, translational science and quantitative analysis, successfully developing collaborations with researchers of different areas of biomedical research at several institutions. I am a Research Assistant Professor at the Laboratory of Investigative Dermatology and the co-director of the biostatistics team at the Rockefeller University Clinical and Translational Science Center (CTSA), where I oversee the design of clinical and research protocols and participate in data analysis. I am skilled in multivariate and longitudinal analysis, time series, and pattern recognition and machine learning methods. My long terms goals are to develop robust statistical techniques to mine and integrate complex high throughput data, tailored to the specific disease model, especially on inflammatory skin diseases such as atopic dermatitis.
Bioinformatics, Biostatistics, Gene Expressions, Genetics, Genomics, Inflammation, Systems Biology
MSc, University of Havana. School of Mathematics and Computer Sciences.
MSc, Catholic University of Rio de Janeiro. Computational Statistics Group
PhD, Catholic University of Rio de Janeiro. Computational Statistics Group
Postdoctoral Studies, The Rockefeller University. Laboratory of Mathematical Physics
The Irma T. Hirschl / Monique Weill-Caulier Research Award
Frederick Seitz Fellowship
Woman in Science Postdoctoral Fellowship
National Ph.D Fellowship
Brazilian National Research Council (CNPQ)
National MsC. Fellowship
Brazilian Ministry of Education (CAPES)
Abel Award (Best MSc Thesis)
University of Havana, School of Mathematics and Computer Scs.
Diploma de Oro (graduated with Magna Cum Laude Honor)
University of Havana
Research: clinical trials, biomarkers, system biology approaches, high-dimensional predictive models, high-throughput data integration
Dr. Suarez-Farinas works in the interface of biomedical research, translational science and quantitative analysis, developing robust statistical techniques to mine and integrate complex high-throughput data, tailored to the specific disease model, especially on inflammatory skin diseases. She have extensive experience in clinical trials design and statistical and bioinformatics techniques applied to high throughput data, including microarrays, next generation sequencing data, metabolomics and proteomics.
Dr. Suarez-Farinas’ research focus on using system biology approaches that combine mechanistic clinical trials and genomic data to unravel the pathogenesis of diseases, develop disease biomarkers and define targets for therapeutics.
Using bioinformatics analysis of high-throughput data, she had developed molecular phenotypes in psoriasis and atopic dermatitis that allows to reliably measure treatment response at the molecular level. This phenotypes facilitates faster screening for effective drugs, unambiguously benchmark multiple drugs in terms of the improvements they show at molecular level.
She develops predictive tools that uses genomic data to predict long-term treatment response to psoriasis treatment after a short course of treatment.
Physicians and scientists on the faculty of the Icahn School of Medicine at Mount Sinai often interact with pharmaceutical, device and biotechnology companies to improve patient care, develop new therapies and achieve scientific breakthroughs. In order to promote an ethical and transparent environment for conducting research, providing clinical care and teaching, Mount Sinai requires that salaried faculty inform the School of their relationships with such companies.
Below are financial relationships with industry reported by Dr. Suarez-Farinas during 2020 and/or 2021. Please note that this information may differ from information posted on corporate sites due to timing or classification differences.
- DBV Technologies
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