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Artificial intelligence methods such as deep learning are enabling breakthrough advances in biomedical data analysis. From medical diagnosis and DNA sequence analysis to augmented microscopy and molecular design, the scope of applications for artificial intelligence is constantly expanding and drawing on ever larger datasets. However, most research studies based on deep learning do not enable users to fully adapt such methods to their own data, and making reuse of published methods can be difficult for non-IT specialists. To overcome these obstacles, scientists in the Institut Pasteur's Imaging and Modeling Unit have designed a platform that offers easier access to deep learning for the biomedical community.

ImJoy – powerful but easy to use artificial intelligence tools

Scientists at the Institut Pasteur, in collaboration with the Royal Institute of Technology in Stockholm and Stanford University, have developed ImJoy, a computational platform which aims to make deep learning accessible to the biomedical community and beyond. The platform was designed to offer powerful data analysis tools that are easy to use. "ImJoy enables users without programming skills, both to reuse pretrained neural networks and to train them on new data," explains Christophe Zimmer, head of the Imaging and Modeling Unit at the Institut Pasteur. ImJoy works with various computing environments, including desktop computers, remote servers (cloud computing) and smartphones. Since it requires no Internet access, it can be used to analyze sensitive data. ImJoy can also run programs written in different computer languages (JavaScript, Python, etc.), which can exchange data via dedicated gateways.
To illustrate the potential of ImJoy, the scientists have already implemented a number of tools using deep learning, in order to, for example:

  • improve the quality of microscopy images;
  • segment cell images;
  • analyze the cellular location of proteins;
  • diagnose skin lesions;
  • predict protein affinity with various DNA sequences.

"ImJoy should facilitate the adoption of deep learning in the biomedical community and accelerate the use of big data for scientific discovery and medicine," concludes Christophe Zimmer.

The ImJoy platform, together with its source code, are openly available by clicking here.

Publication link.

More details on Institut Pasteur website.

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