NSF Supports Interdisciplinary Pandemic Prevention Workshops
WID’s John Yin is part of a team assembling February workshops on predictive intelligence for pandemic prevention.
Tag: modeling
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.
Thompson Center Badgercast: Michael Ferris
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.
Researchers Design New Strategy for Gene Therapy Development
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.
Researchers Look to Control Organ Function Through New Computational Model
A cross-institutional team including WID’s John Yin is creating a computational model to guide the development of bladder therapeutics.
Data Science Research Bazaar Seeks Proposals
The Bazaar, happening throughout February, 2021, has the theme Data Science for the Social Good.
UW–Madison to Continue Fundamental Data Science Research with Phase II Award from NSF
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.
WID Researchers Among Data Science Institute Mini Grant Recipients
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.
Researchers at UW–Madison Lead Data Science Coalition to Aid with COVID-19
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.
How a UW-Madison Engineer Could Help Beat a Virus at its Own Game
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.
New Tool Predicts Three-Dimensional Organization of Human Chromosomes
WID researchers have developed a computational tool that can accurately predict the three-dimensional interactions between regions of human chromosomes.
Data Scientists Unite Research and Policy in New Project
A new data science project, “WEREWOLF”, puts powerful modeling tools into the hands of Wisconsin policymakers to create the energy systems of tomorrow.
WID Researchers Collaborate on UW2020 Projects
Researchers at the Wisconsin Institute for Discovery are co-Principal Investigators and co-Investigators on four UW2020: WARF Discovery Initiative projects.
Uncovering a Connection Between Regulators and Genes During Early Neurodevelopment
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.
UW–Madison Researchers Earn Army Research Office Grant to Study Microbial Communication
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 Hubs Launch at Illuminating Connections Event
WID’s new hubs—Data Science, Multi-Omics, and Illuminating Discovery—represent a new path forward for collaborative research projects and fields.
New Technology for Controlling Neural Tissue Manufacturing
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.
Using Data Science to Find the Next El Nino
A new approach to climate data analysis hopes to improve regional forecasts.
Data Science Initiative Supports Faculty Research at UW–Madison
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.
Air Force-Backed Center to Make Machine Learning More Independent, Predictable, Secure
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.
Kinetic Modeling of Virus Growth in Cells
A new paper in Microbiology and Molecular Biology Reviews describes how the steps of virus reproduction contribute to timing and productivity of cell infection.
When Communicating with Color, Balance Can Be a Path to Accuracy
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.
Interdisciplinary Faculty Build Data Science Future in New Institute Based at WID
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.
Connecting the Dots: a New Method to Understand Cell Type Transitions
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.
Inference and Evolutionary Analysis of Genome-Scale Regulatory Networks in Large Phylogenies
In a paper in Cell Systems, Sushmita Roy and colleagues develop a probabilistic graphical model-based method, multi-species regulatory network learning that uses a phylogenetic framework to infer regulatory networks in multiple species simultaneously.
Deciphering Gene Regulatory Networks
Systems Biology researcher Sushmita Roy is leading an effort putting computational methods to work characterizing the gene regulatory networks responsible for cell differentiation.