John Denu

Professor, Multi-Omics Leader

  • WID Faculty

Epigenetic chromatin changes that regulate cell signaling and metabolism

Nicole Piscopo

Nicole Piscopo

  • Graduate Student

High-Content Analysis of Heterogeneity in Manufacturing of Chimeric Antigen Receptor (CAR) T Cells.

Shaoqin (Sarah) Gong

Sarah Gong

Kellett Mid-Career Award 2018-2023
Vilas Distinguished Achievement Professor

  • WID Faculty

Creating nanomedicines and nanomaterials for human health and sustainable energy applications.

ZhengZheng (Jane) Tang

ZhengZheng Tang

Assistant Professor

  • Discovery Fellow

Developing statistical methods and computational tools for high-throughput omics data.

Multi-Omics Hub

The Multi-Omics Hub will focus on the use of big data about the genes, microorganisms, and metabolites to understand biological systems. WID’s expertise makes it an ideal home for the Epigenetics Initiative for the large campus community that studies the epigenome, and as such WID will organize meetings, seminars, mutli-PI …

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.

Rupa Sridharan

Rupa Sridharan

Associate Professor

  • WID Faculty

Epigenetic control of cell identity in pluripotency, development and disease

Krishanu Saha

Kris Saha

Associate Professor

  • WID Faculty

Human cell engineering including CRISPR gene editing and epigenetic reprogramming; science & society

Katie Mueller

Katie Mueller

  • Graduate Student

In vitro modeling of CAR T cell cytotoxicity, activation, and exhaustion.

Randolph Ashton

Randy Ashton

Associate Professor

  • WID Faculty

Engineering brain and spinal cord tissues ex vivo using human pluripotent stem cells

John Yin

John Yin

Vilas Distinguished Achievement Professor

  • WID Faculty

Forecasting of virus-host growth and infection spread; physical and chemical origins of life

Understanding the Immune System with Machine Learning

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.