GIF Talk “Biomedical Data Science: From Big Data to Small Molecule Drug Discovery and Repurposing”
On October 17, Russian-Armenian University hosted Dr. Alexander Tropsha with a GIF Talk “Biomedical Data Science: From Big Data to Small Molecule Drug Discovery and Repurposing” within the Global Innovation Forum 2019: Transforming Intelligence. The series of GIF Talks are designed to give an opportunity to students of the Armenian universities to meet and learn from the brightest scientists.
Dr. Tropsha discussed several topics of relevance regarding accurate predictions of chemical bioactivity, data curation, methods, models and approaches to bioactivity prediction and elucidation of the mechanisms of action (MOA) of bioactive compounds and approaches to de novo design of new chemicals with the desired properties.
“Besides solely analyzing the data, we need to think about where the data comes from, how it should be analyzed and whether or not we can actually trust it”, he highlighted. He later elaborated on data sources, which can vary from scientific literature to social media. Dr. Tropsha mentioned that discoveries can be made right in the library by analyzing scientific texts. Social media can serve as a basis for analysis, too. He gave the example of researchers identifying a restaurant in New York where people got food poisoning by analyzing thousands of posts and locating those of people complaining.
He also illustrated best practices for data curation and model development and then described the Biomedical Data Translator and Reasoning project funded by the NIH. In this project, they integrate data in multiple biomedical databases, or knowledge sources, into a comprehensive Knowledge Graph where individual biomedical entities such as drugs, biological targets of drug action and diseases form nodes, and functional relationships between these entities are encoded as edges.
Dr. Alexander Tropsha is a K.H. Lee Distinguished Professor and Associate Dean for Pharmacoinformatics and Data Science at the UNC Eshelman School of Pharmacy. His research interests are in the areas of Computational drug discovery, Cheminformatics, and Structural Bioinformatics. He has authored more than 230 peer-reviewed research papers, reviews and book chapters.
Photos: M.G. Sarkisov.