Modeling-based Evaluation of the Potential of Takeda Oncology Compounds for Treatment of COVID-19

Discrete State Modeling and Knowledge Acquisition to Investigate Human Immune Response Juilee Thakar University of Rochester Medical Center Abstract: Human immune response is complex interplay of molecular and cellular responses to signals. The wide range of signals such as viruses and vaccines elicit cascades of signaling events, which can be measured using highly advanced high-throughput assays. We have developed tools to construct mechanistic models of these signaling cascades using omics datasets. The mechanistic models are developed using parameter-free discrete-state methods and reveal multiple different states of cellular phenotype driven by molecular pathways. However, one caveat is in retrieving high-quality frequently updated topological maps of molecular and cellular information. This talk will briefly introduce the mechanistic modeling methodology and will drive discussion on knowledge acquisition in context to molecular and cellular pathways. If you found this video useful, please check out our other videos on computational modeling, infection and immunology: https://youtube.com/playlist?list=PLiEtieOeWbMKh9VcQoinSwODcSZKMTGat Please consider joining our IMAG/MSM WG on Multiscale Modeling and Viral Pandemics: https://www.imagwiki.nibib.nih.gov/content/msm-viral-pandemics-meetings Please also consider joining the Global Alliance for Immune Prediction and Intervention: http://glimprint.org/