The Imageomics Institute GitHub organization hosts the development and distribution of a collection of open-source ML tools used to study the biological information encoded in images and videos integrated with structured biological knowledge. All Imageomics code, data, models, and demos hosted on GitHub or Hugging Face are searchable through the Imageomics Catalog:
The Imageomics Institute is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) program under Award #2118240 (Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning). It started in Oct 2021.
You can find a full mission, vision, and abstract under the Imageomics website's About page. In short, the vision of the Institute is to "establish a new scientific field called imageomics that harnesses revolutions in data science and computing, as well as the rapidly expanding collections of biological image data, in order to accelerate biological understanding of phenotypic traits extracted from images of organisms."
The inception and research of the Imageomics Institute builds heavily on the "Biology-Guided Neural Networks for Discovering Phenotypic Traits" (BGNN) project, also funded by the US National Science Foundation. BGNN itself built in part on the Phenoscape project (funded by NSF multiple times), which started in 2007 and was incubated at the NSF-funded National Evolutionary Synthesis Center (NESCent).
Due to the history (see above) and highly collaborative and cross-disciplinary nature of the Institute, important software products and other code repositories are distributed over several organizations in GitHub, in addition to the ones found here. The following gives an overview and useful links.
Disclaimer: Any opinions, findings and conclusions or recommendations expressed in the materials here are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.