Roles
- Professor of Molecular and Cellular Pharmacology
- Director of Digital Drug Discovery, Institute for Data Science & Computing
- Associate Director of Data Science, Sylvester Comprehensive Cancer Center
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Biography
Dr. Schürer studied chemistry at Humboldt University of Berlin and University of California Berkeley. Following his PhD from the Technical University Berlin, he built and directed the international operations to the develop life science information technology and scientific content products at Libraria and Eidogen-Sertanty Inc, two technology startups in San Jose California where he was a founding member. After building the operational and discovery cheminformatics platform at Scripps Florida to support Scripps Drug Discovery and the Scripps Molecular Libraries Screening and Probe Discovery Program, he started his academic career at the University of Miami. At Miami he developed the BioAssay Ontology (BAO) which has become the de-facto standard to describe drug discovery assays and is widely used across the industry. Among numerous research collaborations, Dr. Schürer has served as Principal Investigator in several national and international research consortia, the Molecular Libraries Program (MLP), Library of Integrated Network-based Cellular Signatures (LINCS), Big Data to Knowledge (BD2K), Illuminating the Druggable Genome (IDG), Rapid Acceleration of Diagnostics (RADx), and Molecular Phenotypes of Null Alleles in Cells (MorPhiC). -
Education & Training
Education
Post Graduate Training
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Honors & Awards
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Teaching Interests
Dr. Schürer teaches introduction to cheminformatics & computational chemistry, bioinformatics, kinase structure and function, and drug development in several graduate programs at the Miller School of Medicine. -
Research Interests
The Schürer Systems Drug Discovery Research Group develops and applies data science approaches across the domains of chemistry, biology, and medicine with applications in drug repositioning and -rescuing, precision combination therapies, and developing novel small molecules with specific biological functions and mechanisms. Our research programs interface data science, cheminformatics, computational biology, and medicinal chemistry. To make large and diverse datasets FAIR (Findable Accessible, Interoperable and Reusable) and enable the development of data-driven and semantic models, our group develops data standards, ontologies, and full stack software applications. -
Publications
Disclaimer: Information presented in this section has been consolidated using AI and machine learning technologies. While every effort has been made to ensure accuracy, errors may occur. If you identify any inaccuracies, use this link to inform our data team. Your feedback is appreciated and helps us improve the quality of our content.Grants & Sponsored Research
ActiveCompleteViewing number of total completed grantsCopyrights & Patents
Professional Activities
Articles & News
Harnessing Supercomputing Power for Drug Discovery
Chan Zuckerberg Initiative Grant Will Diversify Cancer and Normal Tissue Datasets, Improve AI Models
Hope Abounds at First Miami Translational and Clinical Oncology Symposium
Disclaimer:
Information presented in this section has been consolidated using AI and machine learning technologies. While every effort has been made to ensure accuracy, errors may occur. If you identify any inaccuracies, use this link to inform our data team. Your feedback is appreciated and helps us improve the quality of our content.