Luca Romeo, Università Politecnica delle Marche, Ancona, Italy.October 27, 2020. 12:45 – 1:45 pm.A Virtual Seminar on Blackboard Collaborate. Several countries are experiencing sustained local transmission of coronavirus disease (named COVID-19) in people of all ages. Although some people with COVID-19 have mild to moderate symptoms the disease can cause…
Giulia Palermo, Aiding SARS-CoV-2 detection through emerging CRISPR-Cas genome editing technologies
Giulia Palermo, UC Riverside.October 20, 2020. 3:35 – 4:50 pm.A Joint Virtual Seminar with IIT’s Chemistry Colloquium on Blackboard Collaborate. The SARS-CoV-2 coronavirus is rapidly spreading across multiple countries, causing a severe acute respiratory syndrome that threatens the world population. As the number of cases is steadily growing, there is…
Guowei Wei, AI and Math for the Development of COVID-19 Diagnostics, Vaccines, and Drugs
Guowei Wei, Michigan State University.October 13, 2020. 12:45 – 1:45 pm. A Virtual Seminar on Blackboard Collaborate. Artificial intelligence (AI) has fundamentally changed the landscape of science, technology, industry, and social media in the past few years. It holds a great future for the design and discovery of COVID-19 diagnostics,…
Daniel Jacobson, Uncovering the Bradykinin Storm as the mechanism of COVID-19 symptoms using Supercomputing, Explainable-AI and Systems Biology
Daniel Jacobson, Oak Ridge National Laboratory.September 22, 2020. 12:45 – 1:45 pm.A Virtual Seminar on Blackboard Collaborate. Using a Systems Biology approach, we are integrating genomic, transcriptomic, proteomic, and molecular structure information to provide a holistic understanding of the COVID-19 pandemic. A combination of data analytic, statistical and explainable-AI methods…
Michael Mascagni, The “White Rat” of Numerical Reproducibility
Coming Fall 2020 We explore an application from the author’s work in neuroscience. A code used to investigate neural development modeled 100 neurons with all-to-all excitatory connectivity. We used a simple ordinary differential equation system to model each neuron, and this model was used to produce a paper published in the Journal of…
Stephen J. Klippenstein, Ab Initio Kinetics as a Tool for Mapping Chemically Reactive Gas Phase Environments
February 26, 1:50pm, Room 122 John T. Rettaliata Engineering Center Over the last few decades ab initio gas-phase kinetics has transformed from a tool for interpreting experimental data to providing predictions that rival the accuracy of most experiments. This transformation provides many opportunities for utilizing ab initio kinetics in the…
George C. Schatz, Understanding Self-Assembly of Functional Nanostructures
George C. Schatz, Northwestern University.October 12, 2021. 3:35 – 4:50 pm.A Joint Virtual Seminar with IIT’s Chemistry Colloquium on Zoom. Molecular self-assembly involves the use of hydrogen bonds and other noncovalent interactions between molecules to create supramolecular structures. A goal of theory is to be able to predict and understand…
Joseph Orgel, Structural, Experimental and Computational Approaches to the Study of Contemporary and Ancient Tissues Give Modern Insights in Diagnosis and Repair
November 14, 12:45pm, Room 111 Robert A. Pritzker Science Center One of the most serious impediments to the study of traumatic injury is the lack of meaningful primary mechanical damage criteria at the molecular level in TBI, heart ventricular diseases and joint injuries. Similarly so, for conditions based on prolific pathologies, such…
Jinqiao Duan, Data Science Plus Dynamical Systems: What Can We Learn?
November 13, 12:45pm, Room 104 Stuart Building Observational datasets are abundant. Dynamical systems are mathematical models in engineering, medicine and science. Data are noisy and dynamical systems are often under random fluctuations (either Gaussian or non-Gaussian noise). The interactions between data science and dynamical systems are becoming exciting. On the one…
Gal Mishne, Multiway Tensor Analysis with Neuroscience Applications
October 24, 12:45pm, Room 104 John T. Rettaliata Engineering Center Experimental advances in neuroscience enable the acquisition of increasingly large-scale, high-dimensional and high-resolution neuronal and behavioral datasets, however addressing the full spatiotemporal complexity of these datasets poses significant challenges for data analysis and modeling. We propose to model such datasets…