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The goals of this RFA include, but are not limited to:
Developing standard formats and analysis pipelines for genomic, proteomic, and imaging data, in forms that enable consistent use of these pipelines by numerous experimental labs
Identifying and solving common challenges for web-based interactive visualization of cellular and imaging data
Developing user tools that allow scientists and physicians to extract and analyze data organized by genes, cells, or tissues of interest
Supporting analytical methods and machine learning approaches to solving problems such as multimodal integration, inference of state transitions and developmental trajectories, and representation of spatial relationships at the cellular or molecular level
Generating curated benchmark datasets from new or existing data for evaluating computational methods and designing future analysis competitions
Developing new computational approaches to comparing and normalizing genomic and imaging data across assays, subjects, and species
Generating experimental datasets that directly address computationally-guided questions in quality control, reproducibility, or multimodal integration
The text was updated successfully, but these errors were encountered:
Supporting analytical methods and machine learning approaches to solving problems such as multimodal integration, inference of state transitions and developmental trajectories, and representation of spatial relationships at the cellular or molecular level
Generating curated benchmark datasets from new or existing data for evaluating computational methods and designing future analysis competitions
Copied from the RFA
The goals of this RFA include, but are not limited to:
The text was updated successfully, but these errors were encountered: