Modeling is the process of developing and testing mathematical representations of processes or events.
Modeling is foundational to much of the work done at WID, from modeling evolutionary and biological systems to power grids and fish habitats. Researchers at WID work on the fundamental algorithms and formulations that allow them to build the best and most useful models to solve difficult problems.
Modeling is a key tool for WID’s Data Science Hub.
WID's John Yin is part of a team assembling February workshops on predictive intelligence for pandemic prevention.
WID's Michael Ferris joined the Thompson Center on Public Leadership to discuss a data-based planning tool called “Wisconsin Expansion of Renewable Electricity with Optimization under Long-term Forecasts” (WEREWOLF) he developed with Thompson Center faculty research funding.
A promising platform developed by the Saha Lab at WID advances the CRISPR genome editing field and could lead to effective treatments for many diseases.
A cross-institutional team including WID's John Yin is creating a computational model to guide the development of bladder therapeutics.
The Wisconsin Institute for Discovery is home to the Institute for the Foundations of Data Science, which has received Phase II funding from the National Science Foundation.
Jon Eckhardt, Robert Nowak, and Kevin Ponto were among the recipients of nine mini grants from the American Family Insurance Data Science Institute to advance data science.
WID's Data Science Hub is part of the COVID-19 Data Science Research Group that is interpreting data, using that data to create models, and sharing information and findings.
WID's John Yin, who uses experimental and computational methods to understand how viruses spread, is working on several projects that could have a direct bearing on COVID-19.
WID researchers have developed a computational tool that can accurately predict the three-dimensional interactions between regions of human chromosomes.
A new data science project, "WEREWOLF", puts powerful modeling tools into the hands of Wisconsin policymakers to create the energy systems of tomorrow.
Researchers at the Wisconsin Institute for Discovery are co-Principal Investigators and co-Investigators on four UW2020: WARF Discovery Initiative projects.
WID researchers used a collaborative combination of computational and wet lab experimental techniques to find a connection between a transcription factor and a neurodevelopment gene.
WID Director Jo Handelsman and biochemistry professor Ophelia Venturelli are part of a multi-university interdisciplinary team awarded a grant to study information transmission in microbial communities and how biological networks communicate.
WID's new hubs—Data Science, Multi-Omics, and Illuminating Discovery—represent a new path forward for collaborative research projects and fields.
A paper published in eLife this week by an interdisciplinary team at WID describes new methods for reproducibly manufacturing brain and spinal cord organoids with strict control over morphogenic and developmental processes.
A new approach to climate data analysis hopes to improve regional forecasts.
Ten highly innovative projects have been chosen to receive University of Wisconsin–Madison Data Science Initiative funding, including two led by Wisconsin Institute for Discovery investigators.
Much remains mysterious in the realm of machine learning. The next generation of machine learning algorithms is expected to not only bolster national defense capabilities, but also benefit civilians.
A new paper in Microbiology and Molecular Biology Reviews describes how the steps of virus reproduction contribute to timing and productivity of cell infection.
Karen Schloss and Laurent Lessard are working on a method for matching colors to people's expectations to send the right message — starting with the best colors for waste and recycling bins.
The new institute, housed at UW–Madison’s Wisconsin Institute for Discovery (WID), will play a key role in the future of data science, developing fundamental techniques for handling increasingly massive data sets in shorter times.
Wisconsin Institute for Discovery (WID) researchers Rupa Sridharan and Sushmita Roy are combining their expertise in regenerative biology and computational biology to better understand how cells transition from one type to another through gene regulation.
Systems Biology researcher Sushmita Roy is leading an effort putting computational methods to work characterizing the gene regulatory networks responsible for cell differentiation.
Systems Biology researchers Deborah Chasman and Sushmita Roy are using machine learning to identify virus and pathogenicity-specific regulatory networks which may guide the design of effective therapeutics for infectious diseases. The work is described in a recent paper in PLOS Computational Biology.
Professor Thomas Rutherford, WID Optimization, and colleagues used numerical models to examine whether the threat of carbon tariffs might lower the cost of reductions in world carbon emissions in a paper published in the February issue of the American Economic Journal: Economic Policy.
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