ImJoy

ImJoy enables execution and deployment of deep learning models and plugins for biomedical image analysis and genomics.


Key Features:

  • Deep Learning Plugins: Support for a variety of plugins that run deep learning models for biomedical analyses.
  • Mobile and Interactive Image Analysis: Specialized plugins provide interactive image analysis workflows that can operate in mobile or interactive contexts.
  • Genomics Analysis: Plugins facilitate deep-learning-based analysis of genetic data, including sequence analysis, variant calling, and functional annotation.
  • Plugin Deployment and Development: Capability to deploy pre-built solutions or develop custom plugins to integrate and run computational models.

Scientific Applications:

  • Biomedical image analysis: Application of deep learning models to analyze and interpret biological and microscopy images.
  • Sequence analysis: Use of deep learning approaches for analyzing nucleotide sequence data.
  • Variant calling and functional annotation: Deep-learning-enabled workflows for identifying genetic variants and annotating their potential functions.

Methodology:

Execution of deep learning models via plugins to perform image analysis and genomics tasks, including sequence analysis, variant calling, and functional annotation.

Topics

Details

Tool Type:
web application
Added:
1/14/2020
Last Updated:
4/16/2021

Operations

Data Inputs & Outputs

Publications

Ouyang W, Mueller F, Hjelmare M, Lundberg E, Zimmer C. ImJoy: an open-source computational platform for the deep learning era. Nature Methods. 2019;16(12):1199-1200. doi:10.1038/s41592-019-0627-0. PMID:31780825.

PMID: 31780825
Funding: - Fondation pour la Recherche Médicale: DEQ 20150331762 - Knut och Alice Wallenbergs Stiftelse: 2016.0204 - Familjen Erling-Perssons Stiftelse: 20180316 - Vetenskapsrådet: 2017-05327 - Forskningsrådet om Hälsa, Arbetsliv och Välfärd: 2017-0532

Documentation