Tag: complex biological systems
A living system, like any complex entity, is more than the sum of its parts. It can be as simple as a virus or as complex as an ecosystem. Researchers at WID aspire to gain an understanding of how such systems function, as well as how they adapt to and shape their environments over different time scales.
An interdisciplinary group of engineers, computer scientists, physicists, and evolutionary biologists take a multi-pronged approach to understanding living systems. We develop and combine experimental and computational methods to study diverse problems, ranging from interactions between organisms (e.g., between hosts and pathogens, and within diverse microbial communities) and interaction networks within organisms (e.g., regulatory and metabolic interactions). A common theme to complex biological systems research at WID is to view these systems through the lens of evolution.
Talia Sankari
Methods of chemical ecosystem selection which may have led to the origins of life on prebiotic Earth
Christopher Endemann
Data Science Facilitator
Facilitating connections and training researchers in data science.
WID alumnus awarded first AAAS Science & Technology Policy Fellowship in the U.S. Department of the Treasury
WID and Saha Lab alumnus, and current postdoc at the Morgridge Institute for Research, Amritava Das anticipates that he will put his engineering and bioscience training to use exploring the sometimes knotty connections between science, national security, and finance.
Tolulope Perrin-Stowe
Relationship between genomes and their environments to predict organisms' fitness correlations.
Molecular Puzzles in 3D: Understanding a Mechanism for Methylation
A new publication from the Xuehua Zhong’s group at the Wisconsin Institute for Discovery and the genetics department at the University of Wisconsin–Madison clarifies an important epigenetic mechanism in plants that will help researchers better understand the epigenomes of both plants and animals.
Undergraduate Researcher Helps Fill in the Blanks on Virus Lifecycle
Tianyi “Herry” Jin, an undergraduate in John Yin’s lab group at WID and the department of chemical and biological engineering, published discoveries about viruses in the journal Integrative Biology.
NSF Supports Interdisciplinary Pandemic Prevention Workshops
WID’s John Yin is part of a team assembling February workshops on predictive intelligence for pandemic prevention.
UW Researchers Partner with US Department of Defense to Develop Stem Cell Therapy for Combat-Related Eye Injuries
Using an ingenious microscopic retinal patch, eye researchers at UW‒Madison will develop and test a new way to treat United States military personnel blinded in combat. WID’s Sarah Gong is a collaborator on the project.
Randolph Ashton and Collaborators Win WARF Innovation Award
WID’s Randolph Ashton, Gavin Knight, Benjamin Knudsen, and Nisha Iyer take top honors from the Wisconsin Alumni Research Foundation’s Innovation Awards. Their work, Superior Neural Tissue Models for Disease Modeling, Drug Development and More, was selected from more than 400 innovation disclosures.
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.
New Effective and Safe Antifungal Isolated from Sea Squirt Microbiome
By combing the ocean for antimicrobials, scientists at the University of Wisconsin–Madison have discovered a new antifungal compound that efficiently targets multi-drug-resistant strains of deadly fungi without toxic side effects in mice. WID postdoc Marc Chevrette is part of the team that published the finding in Science.
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.
Saptarshi Pyne
Development of computational methods for inference and analysis of biological networks
Yunyi Shen
Graduate Assistant
Statistical models that reconstruct the interaction networks among microbes and experimental design