Chan Zuckerberg Initiative announces nearly $28 million for visual proteomics

Today, the Chan Zuckerberg Initiative (CZI) announced nearly $28 million in grants to support technology developments that will allow researchers to see the inner workings of cells at near-atomic resolution through next-generation electron microscopy. CZI also launched a new funding opportunity to support plugin development projects for the napari image analysis platform, a community-built, Python-based, open source tool for browsing, annotating, and analyzing large multi-dimensional images.

The Frontiers of Imaging initiative, part of CZI's broader Imaging program, supports the development of disruptive imaging technologies that connect biological scales across organs, cells, and proteins, allowing researchers to directly visualize biological processes at the necessary resolution and context to obtain a mechanistic understanding of health and disease.

The 14 selected grantees from the Visual Proteomics Request for Applications (RFA) will work on 2 1/2-year technology projects that will allow researchers to obtain unprecedented views of the structure, quantity, distribution, and interactions of proteins in cells. Projects include improvements to imaging hardware, software development, correlative light and electron microscopy, and imaging probes.

Obtaining high-resolution views of proteins in their cellular environment is a key step to gaining a better understanding of how cells function in normal and diseased states and to creating more effective therapies. We're excited for these talented scientists to develop new imaging technologies to advance visual proteomics."

Cori Bargmann, Head of Science, Chan Zuckerberg Initiative

In a second project, CZI is launching the napari Plugin Accelerator Grants RFA, which aims to generate an extensible plugin ecosystem and provide easy access to reproducible and quantitative bioimage analysis. The rise of Python as a leading platform for scientific computing and machine learning shows promise for applications in biomedicine.

Yet it remains difficult for biologists to take advantage of the latest developments in deep learning-enabled quantitative analysis because of a lack of visualization and analysis tools that can support modern microscopy and large imaging datasets. To address this challenge, CZI partners with napari, a foundational visualization tool that provides access to domain specific analysis through Python plugins developed, maintained, and supported by the bioimaging community.

"We want to identify and support tools that are good models of open source software development practices for a growing community of academic plugin developers," said CZI Science Product Manager Justin Kiggins. "In building this ecosystem of image analysis tools, we're seeking great examples that developers can look to for inspiration--from code quality, to compatibility with other tools in the scientific Python ecosystem, to potential for impact in fields like neurodegeneration and single-cell biology."

To drive development of napari's growing ecosystem of plugins for image analysis and support the maintenance of plugins, CZI invites applications for grants of $20,000 or $50,000 that would enable developers to convert an existing image analysis tool to a napari plugin; sustain and continue development of an existing napari plugin; or build foundational infrastructure for other plugin developers. Learn about the Alfa Cohort of software developers creating plugins for napari.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
VANCE trial marks milestone in t cell therapy for solid tumors