Next Generation File Formats for BioImaging
To support the Bio-Formats user community and develop new formats to make proprietary file formats obsolete.
Project Lead: Jason Swedlow (University of Dundee)
Next Generation Mass Spectrometry with OpenMS
To enable the analysis of thousands of next generation data-independent acquisition (DIA) mass spectrometry measurements by implementing algorithms, visualization tools, and cloud containers based on OpenMS and the OpenSWATH algorithm.
Project Lead: Hannes Rost (University of Toronto)
Next-Generation Movement Monitoring with the DeepLabCut Ecosystem
To enhance the DeepLabCut ecosystem with a new 3D pose module, integration with generative AI (AmadeusGPT), providing codebase and DLC-Live! code upkeep, and continuing our DEI AI Residency Program. Note: This proposal was funded by The Kavli Foundation as part of our co-funded EOSS Cycle 6.
Project Lead: Mackenzie Mathis (Swiss Federal Institute of Technology, Lausanne)
Next-Generation Simulation and Learning in Imaging-Based Biomedicine
To develop and integrate open computational geometry and simulation technology enabling digital twins in biomedicine – next-generation imaging-based modeling, simulation, optimization, and learning. Note: This proposal was funded by Wellcome Trust as part of our co-funded EOSS Cycle 6.
Project Lead: Marie E. Rognes (Simula Research Laboratory)
Nextflow and nf-core
To keep the current momentum of initiatives and push forward with new actions for accessibility, internationalization, mentorships and ambassadors.
Project Lead: Ellen Sherwood (KTH Royal Institute of Technology)
Papyri: Better Documentation for the Scientific Ecosystem in Jupyter
To upgrade the interactive documentation experience of IPython and Jupyter to allow inline graphs, navigation, and indexing, and to support features currently only available on hosted websites.
Project Lead: Matthias Bussonnier (NumFOCUS, Quansight Labs)
Performance Boosts and Updated Algorithms in NetworkX
To update NetworkX algorithms, increase performance of key biomedically related tools such as community detection (CD) and subgraph-isomorphism (SI), and develop a roadmap for improved visualization. Note: This proposal was funded by Wellcome Trust as part of our co-funded EOSS Cycle 6.
Project Lead: Daniel Schult (Colgate University)
PhasorPy: A Python Library for Phasor Analysis of FLIM and Spectral Imaging
To develop an open Python library and community between spectroscopy and fluorescence microscopy users that is both accessible and self-sustainable in the long term.
Project Lead: Leonel Malacrida (Institut Pasteur Montevideo)
Predictive Modeling of Single-Cell Multiomics Over Time and Space
To develop an end-to-end, predictive computational ecosystem for quantitative spatiotemporal modeling of spatial and single-cell multiomics.
Project Lead: Jonathan Weissman (Whitehead Institute for Biomedical Research)