Friday, September 23, 2022 12:00pm to 1:00pm
About this Event
Abstract: The amount of data produced by experimental laboratories studying biological systems is increasing at an incredible rate. These results are disseminated in a growing number of publishing venues, thus scattering the knowledge and limiting the effectiveness of, or even rendering impractical, the manual analysis of all available information. This highlights the need for automated methods to retrieve and connect related pieces of the voluminous and fragmented knowledge, for the purpose of understanding, explaining, and predicting the behavior of studied systems. Integration of machine reading, automated assembly and analysis of computational models is expected to have a great impact on understanding and efficient explanation of complex biological systems. State-of-the-art machine reading methods extract, in hours, hundreds of thousands of events from the biomedical literature; however, many of the automatically extracted events, which usually represent biological component interactions, are incorrect or not relevant in the context of the modeled system. Therefore, automated methods are necessary to filter and select accurate and useful information from the large machine reading output. In this talk, I will present DySE, the Dynamic System Explanation framework, and several tools that my lab has developed, to efficiently filter, classify, and select the best candidate interactions for model assembly and recommendation. Our tools help reduce the time required for processing machine reading output by several orders of magnitude, and therefore, enable very fast iterative model assembly and analysis. These tools, together with a stochastic simulator for heterogeneous models, statistical model checker, and a sensitivity and path analysis tool, have been used in studies of pancreatic cancer, colon cancer, glioblastoma, and ovarian cancer, and in modeling of immune system cells in tumor microenvironment.
Bio: Dr. Miskov-Zivanov is an Assistant Professor of Electrical and Computer Engineering, at the University of Pittsburgh, with secondary appointments in Bioengineering and Computational and Systems Biology. She received her Ph.D. and M.S. degrees in Electrical and Computer Engineering from Carnegie Mellon University, and her B.S. degree in Electrical Engineering and Computer Science from the University of Novi Sad, Serbia. Prior to her current position, she was a postdoctoral researcher in Computational Biology at the University of Pittsburgh, and in Computer Science at Carnegie Mellon University. Dr. Miskov-Zivanov’s research focuses on the development of methods and tools that enable fast information retrieval, model assembly and recommendation, and efficient and reliable explanations and predictions of dynamic system behavior. She is especially interested in methods that bridge engineering and biology, and she has applied her work in the domains of immunology, cancer, and synthetic biology.
Please let us know if you require an accommodation in order to participate in this event. Accommodations may include live captioning, ASL interpreters, and/or captioned media and accessible documents from recorded events. At least 5 days in advance is recommended.
Registration Link: https://pitt.zoom.us/meeting/register/tJctce-rrj0uHdaXqJFi8zvzEOFuBHHxyQdx