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        "author": "EMMAA developers, Harvard Medical School",
        "author_email": "benjamin_gyori@hms.harvard.edu",
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        "description": "# EMMAA\nEMMAA is an Ecosystem of Machine-maintained Models with Automated Analysis.\nThe primary way users can interact with EMMAA is by using the EMMAA Dashboard\nwhich can be accessed \n[here](http://emmaa.indra.bio).\n\n## Documentation\nFor a detailed documentation of EMMA, visit http://emmaa.readthedocs.io.\nThe documentation contains three main sections:\n- A conceptual description of the [EMMAA architecture and approach](https://emmaa.readthedocs.io/en/latest/architecture/index.html)\n- An [introduction to the EMMAA Dashboard](https://emmaa.readthedocs.io/en/latest/dashboard/index.html)\n- A [module-level documentation of all of EMMAA's code base](https://emmaa.readthedocs.io/en/latest/modules/index.html) linked directly to the source code on Github\n\n## Concept\nThe main idea behind EMMAA is to create a set of computational models that\nare kept up-to-date using automated machine reading, knowledge-assembly, and\nmodel generation. Each model starts with a prior network of relevant concepts\nconnected through a set of known mechanisms. This set of mechanisms is then\nextended by reading literature or other sources of information each day,\ndetermining how new information relates to the existing model, and then\nupdating the model with the new information.\n\nModels are also available for automated analysis in which relevant queries\nthat fall within the scope of each model can be automatically mapped\nto structural and dynamical analysis procedures on the model. This allows\nrecognizing and reporting changes to the model that result in meaningful\nchanges to analysis results.\n\n## Applications\nThe primary application area of EMMAA is the molecular biology of cancer,\nhowever, it can be applied to other domains that the INDRA system and the\nreading systems integrated with INDRA can handle.\n\n## Installation\nUsers primarily interact with EMMAA via the\n[Dashboard](http://emmaa.indra.bio), for which no dependencies need to be\ninstalled.\n\nTo set up programmatic access to EMMAA's features locally, do the following:\n```\ngit clone https://github.com/indralab/emmaa.git\ncd emmaa\npip install git+https://github.com/sorgerlab/indra.git\npip install git+https://github.com/indralab/indra_db.git\npip install -e .\n```\n\nA Dockerized version of EMMAA is available at\nhttps://hub.docker.com/r/labsyspharm/emmaa, which can be obtained as\n```\ndocker pull labsyspharm/emmaa\n```\n\n## Funding\nThe development of EMMAA is funded under the DARPA Automating Scientific\nKnowledge Extraction (ASKE) program under award HR00111990009.\n\n\n",
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