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.

WID Researchers Showcase “Virtual Diary Farm Brain” at American Dairy Science Association Meeting

By combining information from many farms, predictive models and analytic tools can be developed to help producers and consultants navigate, visualize. and analyze the data they are getting from an increasing number of sources to support better management decisions.

Jeff Linderoth

Jeffrey Linderoth

Professor and Department Chair

  • Discovery Fellow

Models and Algorithms for Large-Scale Numerical Optimization

Page Lab

Algorithms for data mining and machine learning, and their applications to biomedical data, especially clinical and high-throughput genetic and other molecular data. Of particular interest are inductive logic programming (ILP) and other multi-relational learning techniques capable of dealing with complex data points (such as molecules or clinical histories) and producing logical rules.

Vetsigian Lab

Dynamics of microbial interactions in natural and synthetic microbial communities. The lab develops protocols for quantifying the community dynamics at the phenotypic and genetic levels, and seek simplified theoretical models that reproduce aspects of the experimentally measured dynamics.

Roy Lab

A computational biology group interested in developing statistical computational methods to understand regulatory networks driving cellular functions. The lab works to identify networks under different environmental, developmental and evolutionary contexts, comparing these networks across contexts, and construct predictive models from these networks.

Loewe Lab

Envisioning new ways to help biologists capture their ideas as models in the larger context of Evolutionary Systems Biology. Our lab aims to improve the quality of these models by quantifying evolution with increasing precision.

Laurence Loewe

Laurence Loewe

Assistant Professor

  • WID Faculty

Developing a stable, user-friendly programming language compiler for reproducible biodata analyses and general modeling in biology while building in-depth models for bioresearch

Adam Christensen

Adam Christensen

Assistant Scientist

  • Research Staff

Building optimization models that help untangle issues of environmental sustainability.