Tag: Gitter Lab

‘Listen to what the flies tell us’

The Drummond-Barbosa Lab looks to the tiny fruit fly to understand big complex questions about the relationship between stem cell development and changes in diet, metabolism, and the environment.

AI protein-prediction tool AlphaFold3 is now open source

via Nature

Morgridge Investigator Anthony Gitter provides comments to Nature News on the importance of open-source code as for-profit companies wade into the academic field of AI research.

Grad student contemplates open-source conflicts with new AI software

Bryce Johnson, a graduate student in the Gitter Lab at Morgridge, published an opinion piece in Undark commenting on open-source conflicts with Google DeepMind’s AI software AlphaFold 3.

Congratulations to our 2024 graduates

Congratulations to our 2024 graduating students and research staff moving on into their next chapters.

Gitter honored with inaugural Jeanne M. Rowe Chair in Virology

Tony Gitter, a Morgridge investigator in virology and research computing and an associate professor of biostatistics and medical informatics at the University of Wisconsin–Madison, has been named the Jeanne M. Rowe Chair in Virology.

Researchers illuminate HIV in cell-to-cell attack mode

When cells infected with HIV make contact with uninfected cells, a new study reveals how that connection unleashes a hornet’s nest of activity that helps drive transmission.

Fire up the GPUs: UW–Madison, Morgridge project sparks next-level computing

A UW 2020 project led by Anthony Gitter has led to a powerful new campus resource for GPU-based computing — the new go-to strategy for complex machine learning research.

How COVID-19 shaped the evolution of a collaborative manuscript writing tool

The COVID-19 pandemic and our tech-driven world have highlighted the need for accessibility of research and efficiency of science publishing. Manubot is one tool that could change the game.

Building better proteins with machine learning

Morgridge Investigator Anthony Gitter and his team are tackling big problems (and big datasets) with machine learning. A new study demonstrates how these tools can be used to predict new protein sequences that could improve protein function.

Machine learning guiding early drug discovery process

via WisBusiness

Morgridge Investigator Anthony Gitter presented at the annual BioForward Biohealth Summit about ways machine learning is having a major impact on the early phases of drug discovery.

Researchers, UW educators see bright future for AI in healthcare

via The Cap Times

Anthony Gitter, a Morgridge investigator, discussed his lab’s promising new efforts to use AI to create custom-fit chemicals — or as he described it, “a brand new recipe” for treating illnesses.

Chemical Legos: A machine learning approach to faster drug discovery

Virtual chemical libraries are capable of producing billions of never-before-synthesized chemical combinations, advancing the quest for beneficial new drugs. Machine learning models are helping find the best candidates.

Machine learning our way through a billion-chemical library

Inspired by the need for smarter and cheaper ways to screen chemicals for potential therapeutic targets, Morgridge investigator Anthony Gitter is finding answers with machine learning tools.

Seize the Moment: Adapting old tools for a novel coronavirus

Morgridge scientists John Brubacher, Anthony Gitter, Brian Bockelman, Ben Cox and Katie Overmyer, joined Gabriella Gerhardt on July 22 for a Fearless Science webinar about rapidly applying technology and methods to answer COVID-19 questions.

Overcoming COVID-19 and future pandemics: new tools to control viral threats

In light of the COVID-19 pandemic, Paul Ahlquist and Tony Gitter joined CEO Brad Schwartz in a webinar where they discussed COVID-19 and the broader context of viral pandemics and how we respond to them.

Chronicling pandemic science in real time

Morgridge virology investigator Anthony Gitter, an assistant professor of biostatistics and medical informatics at UW–Madison, has co-developed a software tool called Manubot to help orchestrate a rapid expert assessment of COVID-19 diagnostics and therapeutics.

‘Protein Pinball’ machine illuminates intricacies of bioinformatics research

Anthony Gitter faced a challenge: How could he translate his work into something children could understand and maybe even enjoy? The answer to that question: ‘protein pinball.’

Scholarly snowball: Deep learning paper generates big online collaboration

Bioinformatics professors Anthony Gitter and Casey Greene set out in summer 2016 to write a paper about the “state of the art” in deep learning for biomedicine, a hot new artificial intelligence field striving to mimic the neural networks of the human brain.

You may also like … Algorithms that improve drug discovery

Anthony Gitter, a Morgridge investigator and assistant professor of biostatistics and medical informatics, says the goal will be to create machine learning tools that dramatically reduce the time and cost associated with screening compounds for therapeutic relevance.

CAREER award to explore dynamics of biology

Anthony Gitter remembers the mental spark when listening to a recent talk about the discovery of so-called “precocious cells” — a tiny group of cells that lead an advance charge against infection.

A pathway for understanding cancer’s origin

The tools of modern biology have made it possible to obtain an incredibly detailed picture of how cancer cells differ from healthy cells at the molecular level. Somewhat paradoxically, despite these meticulous portraits of cancer, it remains remarkably difficult to answer the very fundamental question: What caused cancer in this patient?

Anthony Gitter: Taking the statistical road less traveled

Much of biostatistics involves finding and mapping the predictable pathways that can tell us something about what makes a disease tick. But Anthony Gitter finds equal importance in the statistical back roads that other scientists might ignore.